Estudo longitudinal da compreensão verbal de crianças usuárias de implante coclear

OBJETIVO: analisar a compreensão verbal de crianças surdas usuárias de implante coclear (IC) por meio de um estudo longitudinal. MÉTODOS: os participantes foram nove crianças surdas usuárias de IC. A idade cronológica das crianças variou entre quatro e oito anos e o tempo de uso do IC foi, em média, 1 ano e 6 meses na 1ª avaliação, 3 anos e 7 meses na 2ª avaliação e 4 anos e 9 meses na 3ª avaliação. As crianças foram avaliadas longitudinalmente por meio da Escala de Compreensão Verbal da RDLS. Os materiais usados foram brinquedos, objetos e figuras. Os dados foram analisados qualitativa e quantitativamente. RESULTADOS: os resultados mostraram que as crianças implantadas obtiveram uma evolução estatisticamente significante em relação às habilidades de linguagem receptiva. CONCLUSÃO: o estudo comprova a efetividade do IC para o desenvolvimento da compreensão verbal.

Efeitos da exposição a estímulos aversivos e apetitivos incontroláveis sobre o comportamento verbal em contingências de reforço positivo

Foram analisados efeitos de diferentes histórias de incontrolabilidade por perda ou ganho de pontos sobre o desempenho posterior de participantes humanos na construção de frases. Inicialmente, os participantes podiam ganhar ou perder pontos independentemente de qualquer característica da frase construída. Posteriormente, recebiam pontos por construir frases iniciadas apenas pelo pronome "ele". Os resultados mostram que a exposição à incontrolabilidade pode dificultar condições posteriores de novas aprendizagens sob reforçamento positivo. Interessantemente, essas dificuldades foram menos acentuadas e, em certos casos, até mesmo superadas, no caso de uma história de exposição a ganhos incontroláveis de pontos. Em contrapartida, no caso de uma história de perdas incontroláveis de pontos, aprendizagens subsequentes sob reforço positivo tenderam a ser prejudicadas. Esses resultados contribuem para os estudos de incontrolabilidade e desamparo aprendido, em particular por apresentar alternativas metodológicas passíveis de aplicação a respostas verbais em humanos.

Improving Critical Thinking and Clinical Reasoning With a Continuing Education Course

Background: Continuing education courses related to critical thinking and clinical reasoning are needed to improve the accuracy of diagnosis. Method: This study evaluated a 4-day, 16-hour continuing education course conducted in Brazil. Thirty-nine nurses completed a pretest and a posttest consisting of two written case studies designed to measure the accuracy of nurses` diagnoses. Results: There were significant differences in accuracy from pretest to posttest for case 1 (p = .008) and case 2 (p = .042) and overall (p = .001). Conclusion: Continuing education courses should be implemented to improve the accuracy of nurses` diagnoses. J Contin Educ Nurs 2009;40(3):121-127.

The frontal assessment battery (FAB) reveals neurocognitive dysfunction in substance-dependent individuals in distinct executive domains: Abstract reasoning, motor programming, and cognitive flexibility

Substance-dependence is highly associated with executive cognitive function (ECF) impairments. However. considering that it is difficult to assess ECF clinically, the aim of the present study was to examine the feasibility of a brief neuropsychological tool (the Frontal Assessment Battery FAB) to detect specific ECF impairments in a sample of substance-dependent individuals (SDI). Sixty-two subjects participated in this study. Thirty DSM-IV-diagnosed SDI, after 2 weeks of abstinence, and 32 healthy individuals (control group) were evaluated with FAD and other ECF-related tasks: digits forward (DF), digits backward (DB), Stroop Color Word Test (SCWT), and Wisconsin Card Sorting Test (WCST). SDI did not differ from the control group on sociodemographic variables or IQ. However, SDI performed below the controls in OF, DB, and FAB. The SDI were cognitively impaired in 3 of the 6 cognitive domains assessed by the FAB: abstract reasoning, motor programming, and cognitive flexibility. The FAB correlated with DF, SCWT, and WCST. In addition, some neuropsychological measures were correlated with the amount of alcohol, cannabis, and cocaine use. In conclusion, SDI performed more poorly than the comparison group on the FAB and the FAB`s results were associated with other ECF-related tasks. The results suggested a negative impact of alcohol, cannabis, and cocaine use on the ECF. The FAB may be useful in assisting professionals as an instrument to screen for ECF-related deficits in SDI. (C) 2010 Elsevier Ltd. All rights reserved.

Verbal fluency in the detection of mild cognitive impairment and Alzheimer`s disease among Brazilian Portuguese speakers: the influence of education

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.

A hybrid case adaptation approach for case-based reasoning

Case-Based Reasoning is a methodology for problem solving based on past experiences. This methodology tries to solve a new problem by retrieving and adapting previously known solutions of similar problems. However, retrieved solutions, in general, require adaptations in order to be applied to new contexts. One of the major challenges in Case-Based Reasoning is the development of an efficient methodology for case adaptation. The most widely used form of adaptation employs hand coded adaptation rules, which demands a significant knowledge acquisition and engineering effort. An alternative to overcome the difficulties associated with the acquisition of knowledge for case adaptation has been the use of hybrid approaches and automatic learning algorithms for the acquisition of the knowledge used for the adaptation. We investigate the use of hybrid approaches for case adaptation employing Machine Learning algorithms. The approaches investigated how to automatically learn adaptation knowledge from a case base and apply it to adapt retrieved solutions. In order to verify the potential of the proposed approaches, they are experimentally compared with individual Machine Learning techniques. The results obtained indicate the potential of these approaches as an efficient approach for acquiring case adaptation knowledge. They show that the combination of Instance-Based Learning and Inductive Learning paradigms and the use of a data set of adaptation patterns yield adaptations of the retrieved solutions with high predictive accuracy.