19 resultados para Folklore, Portuguese.
Resumo:
Background: Verbal fluency (VF) tasks are simple and efficient clinical tools to detect executive dysfunction and lexico-semantic impairment. VF tasks are widely used in patients with suspected dementia, but their accuracy for detection of mild cognitive impairment (MCI) is still under investigation. Schooling in particular may influence the subject`s performance. The aim of this study was to compare the accuracy of two semantic categories (animals and fruits) in discriminating controls, MCI patients and Alzheimer`s disease (AD) patients. Methods: 178 subjects, comprising 70 controls (CG), 70 MCI patients and 38 AD patients, were tested on two semantic VF tasks. The sample was divided into two schooling groups: those with 4-8 years of education and those with 9 or more years. Results: Both VF tasks - animal fluency (VFa) and fruits fluency (VFf) - adequately discriminated CG from AD in the total sample (AUC = 0.88 +/- 0.03, p < 0.0001) and in both education groups, and high educated MCI from AD (VFa: AUC = 0.82 +/- 0.05, p < 0.0001; VFf: AUC = 0.85 +/- 0.05, p < 0.0001). Both tasks were moderately accurate in discriminating CG from MCI (VFa: AUC = 0.68 +/- 0.04, p < 0.0001 - VFf:AUC = 0.73 +/- 0.04, p < 0.0001) regardless of the schooling level, and MCI from AD in the total sample (VFa: AUC = 0.74 +/- 0.05, p < 0.0001; VFf: AUC = 0.76 +/- 0.05, p < 0.0001). Neither of the two tasks differentiated low educated MCI from AD. In the total sample, fruits fluency best discriminated CG from MCI and MCI from AD; a combination of the two improved the discrimination between CG and AD. Conclusions: Both categories were similar in discriminating CG from AD; the combination of both categories improved the accuracy for this distinction. Both tasks were less accurate in discriminating CG from MCI, and MCI from AD.
Resumo:
Background: Pain and anxiety are a common problem in all recovery phases after a burn. The Burns Specific Pain Anxiety Scale (BSPAS) was proposed to assess anxiety in burn patients related to painful procedures. Objectives: To assess internal consistency, discriminative construct validity, dimensionality and convergent construct validity of the Brazilian-Portuguese version of the Burns Specific Pain Anxiety Scale. Design: In this cross-sectional study, the original version of the BSPAS, adapted into Brazilian Portuguese, was tested for internal consistency (Cronbach`s Alpha), discriminative validity (related to total body surface area burned and sex), dimensionality (through factor analysis), and convergent construct validity (applying the Visual Analogue Scale for pain and State-Anxiety-STAI) in a group of 91 adult burn patients. Results: The adapted version of the BSPAS displayed a moderate and positive correlation with pain assessments: immediately before baths and dressings (r = 0.32; p < 0.001), immediately after baths and dressings (r = 0.31; p < 0.001) and during the relaxation period (r= 0.31; p < 0.001) and with anxiety assessments (r = 0.34; p < 0.001). No statistically significant differences were observed when comparing the mean of the adapted version of the BSPAS scores with sex (p = 0.194) and total body surface area burned (p = 0.162) (discriminative validity). The principal components analysis applied to our sample seems to confirm anxiety as one single domain of the Brazilian-Portuguese version of the BSPAS. Cronbach`s Alpha showed high internal consistency of the adapted version of the scale (0.90). Conclusion: The Brazilian-Portuguese version of the BSPAS 9-items has shown statically acceptable levels of reliability and validity for pain-related anxiety evaluation in burn patients. This scale can be used to assess nursing interventions aimed at decreasing pain and anxiety related to the performance of painful procedures. (c) 2010 Elsevier Ltd. All rights reserved.
Resumo:
The amount of textual information digitally stored is growing every day. However, our capability of processing and analyzing that information is not growing at the same pace. To overcome this limitation, it is important to develop semiautomatic processes to extract relevant knowledge from textual information, such as the text mining process. One of the main and most expensive stages of the text mining process is the text pre-processing stage, where the unstructured text should be transformed to structured format such as an attribute-value table. The stemming process, i.e. linguistics normalization, is usually used to find the attributes of this table. However, the stemming process is strongly dependent on the language in which the original textual information is given. Furthermore, for most languages, the stemming algorithms proposed in the literature are computationally expensive. In this work, several improvements of the well know Porter stemming algorithm for the Portuguese language, which explore the characteristics of this language, are proposed. Experimental results show that the proposed algorithm executes in far less time without affecting the quality of the generated stems.