36 research outputs found

    Searching PubMed during a Pandemic

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    BACKGROUND: The 2009 influenza A(H1N1) pandemic has generated thousands of articles and news items. However, finding relevant scientific articles in such rapidly developing health crises is a major challenge which, in turn, can affect decision-makers' ability to utilise up-to-date findings and ultimately shape public health interventions. This study set out to show the impact that the inconsistent naming of the pandemic can have on retrieving relevant scientific articles in PubMed/MEDLINE. METHODOLOGY: We first formulated a PubMed search algorithm covering different names of the influenza pandemic and simulated the results that it would have retrieved from weekly searches for relevant new records during the first 10 weeks of the pandemic. To assess the impact of failing to include every term in this search, we then conducted the same searches but omitted in turn "h1n1," "swine," "influenza" and "flu" from the search string, and compared the results to those for the full string. PRINCIPAL FINDINGS: On average, our core search string identified 44.3 potentially relevant new records at the end of each week. Of these, we determined that an average of 27.8 records were relevant. When we excluded one term from the string, the percentage of records missed out of the total number of relevant records averaged 18.7% for omitting "h1n1," 13.6% for "swine," 17.5% for "influenza," and 20.6% for "flu." CONCLUSIONS: Due to inconsistent naming, while searching for scientific material about rapidly evolving situations such as the influenza A(H1N1) pandemic, there is a risk that one will miss relevant articles. To address this problem, the international scientific community should agree on nomenclature and the specific name to be used earlier, and the National Library of Medicine in the US could index potentially relevant materials faster and allow publishers to add alert tags to such materials

    Cultural adaptation and validation of the Health Literacy Questionnaire (HLQ): robust nine-dimension Danish language confirmatory factor model

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    Health literacy is an important construct in population health and healthcare requiring rigorous measurement. The Health Literacy Questionnaire (HLQ), with nine scales, measures a broad perception of health literacy. This study aimed to adapt the HLQ to the Danish setting, and to examine the factor structure, homogeneity, reliability and discriminant validity. The HLQ was adapted using forward-backward translation, consensus conference and cognitive interviews (n = 15). Psychometric properties were examined based on data collected by face-to-face interview (n = 481). Tests included difficulty level, composite scale reliability and confirmatory factor analysis (CFA). Cognitive testing revealed that only minor re-wording was required. The easiest scale to respond to positively was \u27Social support for health\u27, and the hardest were \u27Navigating the healthcare system\u27 and \u27Appraisal of health information\u27. CFA of the individual scales showed acceptably high loadings (range 0.49-0.93). CFA fit statistics after including correlated residuals were good for seven scales, acceptable for one. Composite reliability and Cronbach\u27s α were >0.8 for all but one scale. A nine-factor CFA model was fitted to items with no cross-loadings or correlated residuals allowed. Given this restricted model, the fit was satisfactory. The HLQ appears robust for its intended application of assessing health literacy in a range of settings. Further work is required to demonstrate sensitivity to measure changes

    FACILICODE (Facilitated Work Based Learning)

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    The European Council in 2000 concluded that it is a strategic goal for the European Union (EU) to be the most competitive and dynamic knowledge-based economy in the world. To fulfill this strategy education and continuing education (lifelong learning) has a very high priority. In the enlarged European Union there are 23 million small and medium-sized enterprises (SMEs) representing 99 per cent of all EU enterprises and employing more than 75 million people, according to ‘The New SME Definition – User Guide and Model Declaration’, 200

    Fludarabine, cytarabine, granulocyte colony-stimulating factor, and idarubicin with gemtuzumab ozogamicin improves event-free survival in younger patients with newly diagnosed aml and overall survival in patients with npm1 and flt3 mutations

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    Purpose To determine the optimal induction chemotherapy regimen for younger adults with newly diagnosed AML without known adverse risk cytogenetics. Patients and Methods One thousand thirty-three patients were randomly assigned to intensified (fludarabine, cytarabine, granulocyte colony-stimulating factor, and idarubicin [FLAG-Ida]) or standard (daunorubicin and Ara-C [DA]) induction chemotherapy, with one or two doses of gemtuzumab ozogamicin (GO). The primary end point was overall survival (OS). Results There was no difference in remission rate after two courses between FLAG-Ida + GO and DA + GO (complete remission [CR] + CR with incomplete hematologic recovery 93% v 91%) or in day 60 mortality (4.3% v 4.6%). There was no difference in OS (66% v 63%; P = .41); however, the risk of relapse was lower with FLAG-Ida + GO (24% v 41%; P < .001) and 3-year event-free survival was higher (57% v 45%; P < .001). In patients with an NPM1 mutation (30%), 3-year OS was significantly higher with FLAG-Ida + GO (82% v 64%; P = .005). NPM1 measurable residual disease (MRD) clearance was also greater, with 88% versus 77% becoming MRD-negative in peripheral blood after cycle 2 (P = .02). Three-year OS was also higher in patients with a FLT3 mutation (64% v 54%; P = .047). Fewer transplants were performed in patients receiving FLAG-Ida + GO (238 v 278; P = .02). There was no difference in outcome according to the number of GO doses, although NPM1 MRD clearance was higher with two doses in the DA arm. Patients with core binding factor AML treated with DA and one dose of GO had a 3-year OS of 96% with no survival benefit from FLAG-Ida + GO. Conclusion Overall, FLAG-Ida + GO significantly reduced relapse without improving OS. However, exploratory analyses show that patients with NPM1 and FLT3 mutations had substantial improvements in OS. By contrast, in patients with core binding factor AML, outcomes were excellent with DA + GO with no FLAG-Ida benefit

    Litteratur om Tanzania : Annoteret bibliografi

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    INDHOLD: 1. Generelt om Tanzania -- Historie -- Politik -- Økonomi -- Folk, kvindens stilling, religion, sundhed, uddannelse --Regionalstudier -- Sprog -- Kunst og litteratur -- Zanzibar – 2. Bibliografier -- Tidsskrifter -- 3. Forfatterregister -- Titelregister -- 4. Danske bistandsmidlers anvendelse i Tanzania -- 5. Supplement </p

    Enhancing the Effectiveness of Consumer-Focused Health Information Technology Systems Through eHealth Literacy:A Framework for Understanding Users' Needs

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    Background: eHealth systems and applications are increasingly focused on supporting consumers to directly engage with anduse health care services. Involving end users in the design of these systems is critical to ensure a generation of usable and effectiveeHealth products and systems. Often the end users engaged for these participatory design processes are not actual representativesof the general population, and developers may have limited understanding about how well they might represent the full range ofintended users of the eHealth products. As a consequence, resulting information technology (IT) designs may not accommodatethe needs, skills, cognitive capacities, and/or contexts of use of the intended broader population of health consumers. This mayresult in challenges for consumers who use the health IT systems, and could lead to limitations in adoption if the diversity of userattributes has not been adequately considered by health IT designers.Objective: The objective of this paper is to propose how users&rsquo;needs and competences can be taken into account when designingnew information and communications technology solutions in health care by expanding the user-task-context matrix model withthe domains of a new concept of eHealth literacy.Methods: This approach expands an existing method for supporting health IT system development, which advocates use of athree-dimensional user-task-context matrix to comprehensively identify the users of health IT systems, and what their needs andrequirements are under differing contexts of use. The extension of this model involved including knowledge about users&rsquo;competences within the seven domains of eHealth literacy, which had been identified based on systematic engagement withcomputer scientists, academics, health professionals, and patients recruited from various patient organizations and primary care.A concept map was constructed based on a structured brainstorm procedure, card sorting, and computational analysis.Results: The new eHealth literacy concept (based on 7 domains) was incorporated as a key factor in expanding theuser-task-context matrix to describe and qualify user requirements and understanding related to eHealth literacy. This resultedin an expanded framework and a five-step process, which can support health IT designers in understanding and more accuratelyaddressing end-users&rsquo; needs, capabilities, and contexts to improve effectiveness and broader applicability of consumer-focusedhealth IT systems. It is anticipated that the framework will also be useful for policy makers involved in the planning, procuring,and funding of eHealth infrastructure, applications, and services.Conclusions: Developing effective eHealth products requires complete understanding of the end-users&rsquo; needs from multipleperspectives. In this paper, we have proposed and detailed a framework for modeling users&rsquo; needs for designing eHealth systemsthat merges prior work in development of a user-task-context matrix with the emerging area of eHealth literacy. This framework is intended to be used to guide design of eHealth technologies and to make requirements explicitly related to eHealth literacy,enabling a generation of well-targeted, fit-for-purpose, equitable, and effective products and systems
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