80 research outputs found
Uncovering treatment burden as a key concept for stroke care: a systematic review of qualitative research
<b>Background</b> Patients with chronic disease may experience complicated management plans requiring significant personal investment. This has been termed ‘treatment burden’ and has been associated with unfavourable outcomes. The aim of this systematic review is to examine the qualitative literature on treatment burden in stroke from the patient perspective.<p></p>
<b>Methods and findings</b> The search strategy centred on: stroke, treatment burden, patient experience, and qualitative methods. We searched: Scopus, CINAHL, Embase, Medline, and PsycINFO. We tracked references, footnotes, and citations. Restrictions included: English language, date of publication January 2000 until February 2013. Two reviewers independently carried out the following: paper screening, data extraction, and data analysis. Data were analysed using framework synthesis, as informed by Normalization Process Theory. Sixty-nine papers were included. Treatment burden includes: (1) making sense of stroke management and planning care, (2) interacting with others, (3) enacting management strategies, and (4) reflecting on management. Health care is fragmented, with poor communication between patient and health care providers. Patients report inadequate information provision. Inpatient care is unsatisfactory, with a perceived lack of empathy from professionals and a shortage of stimulating activities on the ward. Discharge services are poorly coordinated, and accessing health and social care in the community is difficult. The study has potential limitations because it was restricted to studies published in English only and data from low-income countries were scarce.<p></p>
<b>Conclusions</b> Stroke management is extremely demanding for patients, and treatment burden is influenced by micro and macro organisation of health services. Knowledge deficits mean patients are ill equipped to organise their care and develop coping strategies, making adherence less likely. There is a need to transform the approach to care provision so that services are configured to prioritise patient needs rather than those of health care systems
The human keratins: biology and pathology
The keratins are the typical intermediate filament proteins of epithelia, showing an outstanding degree of molecular diversity. Heteropolymeric filaments are formed by pairing of type I and type II molecules. In humans 54 functional keratin genes exist. They are expressed in highly specific patterns related to the epithelial type and stage of cellular differentiation. About half of all keratins—including numerous keratins characterized only recently—are restricted to the various compartments of hair follicles. As part of the epithelial cytoskeleton, keratins are important for the mechanical stability and integrity of epithelial cells and tissues. Moreover, some keratins also have regulatory functions and are involved in intracellular signaling pathways, e.g. protection from stress, wound healing, and apoptosis. Applying the new consensus nomenclature, this article summarizes, for all human keratins, their cell type and tissue distribution and their functional significance in relation to transgenic mouse models and human hereditary keratin diseases. Furthermore, since keratins also exhibit characteristic expression patterns in human tumors, several of them (notably K5, K7, K8/K18, K19, and K20) have great importance in immunohistochemical tumor diagnosis of carcinomas, in particular of unclear metastases and in precise classification and subtyping. Future research might open further fields of clinical application for this remarkable protein family
Linguistics for everyone : an introduction
xviii, 534 p. : ill. ; 24 cm
Linguistics for everyone : an introduction
xxv, 545 p. : ill., map ; 24 cm
Research on Intelligent Synthesis Environments
Four research activities related to Intelligent Synthesis Environment (ISE) have been performed under this grant. The four activities are: 1) non-deterministic approaches that incorporate technologies such as intelligent software agents, visual simulations and other ISE technologies; 2) virtual labs that leverage modeling, simulation and information technologies to create an immersive, highly interactive virtual environment tailored to the needs of researchers and learners; 3) advanced learning modules that incorporate advanced instructional, user interface and intelligent agent technologies; and 4) assessment and continuous improvement of engineering team effectiveness in distributed collaborative environments
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