64 resultados para Cognitive behavioral analysis

em QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast


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To assess the efficacy of trauma-focused cognitive behavioral therapy (TF-CBT) delivered by nonclinical facilitators in reducing posttraumatic stress, depression, and anxiety and conduct problems and increasing prosocial behavior in a group of war-affected, sexually exploited girls in a single-blind, parallel-design, randomized,+ controlled trial.

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The main aim of this study is to investigate the consequences of cross-cultural adjustment in an under researched sample of British expatriates working on International Architectural, Engineering and Construction (AEC) assignments. Adjustment is the primary outcome of an expatriate assignment. According to Bhaskar-Srinivas et al., (2005), Harrison et al., (2004) it is viewed to affect other work related outcomes which could eventually predict expatriate success. To address the scarcity of literature on expatriate management in the AEC sector, an exploratory design was adopted. Phase one is characterised by extensive review of extant literature, whereas phase two was qualitative exploration from British expatriates’ perspective; here seven unstructured interviews were carried out. Further, cognitive mapping analysis through Banaxia decision explorer software was conducted to develop a theoretical framework and propose various hypotheses. The findings imply that British AEC firms could sustain their already established competitive advantage in the global marketplace by acknowledging the complexity of international assignments, prioritising expatriate management and offering a well-rounded support to facilitate expatriate adjustment and ultimately achieve critical outcomes like performance, assignment completion and job satisfaction.

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The main aim of this study is to investigate the consequences of cross-cultural adjustment in an under researched sample of British expatriates working on International Architectural, Engineering and Construction (AEC) assignments. Adjustment is the primary outcome of an expatriate assignment. According to Bhaskar-Srinivas et al., (2005), Harrison et al., (2004) it is viewed to affect other work related outcomes which could eventually predict expatriate success. To address the scarcity of literature on expatriate management in the AEC sector, an exploratory design was adopted. Phase one is characterised by extensive review of extant literature, whereas phase two was qualitative exploration from British expatriatesÕ perspective; here seven unstructured interviews were carried out. Further, cognitive mapping analysis through Banaxia decision explorer software was conducted to develop a theoretical framework and propose various hypotheses. The findings imply that British AEC firms could sustain their already established competitive advantage in the global marketplace by acknowledging the complexity of international assignments, prioritising expatriate management and offering a well-rounded support to facilitate expatriate adjustment and ultimately achieve critical outcomes like performance, assignment completion and job satisfaction.

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Despite pattern recognition methods for human behavioral analysis has flourished in the last decade, animal behavioral analysis has been almost neglected. Those few approaches are mostly focused on preserving livestock economic value while attention on the welfare of companion animals, like dogs, is now emerging as a social need. In this work, following the analogy with human behavior recognition, we propose a system for recognizing body parts of dogs kept in pens. We decide to adopt both 2D and 3D features in order to obtain a rich description of the dog model. Images are acquired using the Microsoft Kinect to capture the depth map images of the dog. Upon depth maps a Structural Support Vector Machine (SSVM) is employed to identify the body parts using both 3D features and 2D images. The proposal relies on a kernelized discriminative structural classificator specifically tailored for dogs independently from the size and breed. The classification is performed in an online fashion using the LaRank optimization technique to obtaining real time performances. Promising results have emerged during the experimental evaluation carried out at a dog shelter, managed by IZSAM, in Teramo, Italy.

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This study investigated the association between different neonatal ultrasonographic classifications and adolescent cognitive, educational, and behavioral outcomes following very preterm birth. Participants included a group of 120 adolescents who were born very preterm (33 weeks of gestation), subdivided into three groups according to their neonatal cerebral ultrasound (US) classifications: (a) normal (N = 69), (b) periventricular hemorrhage (PVH, N = 37), and (c) PVH with ventricular dilatation (PVH + DIL, N = 14), and 50 controls. The cognitive functions assessed were full-scale IQ, phonological and semantic verbal fluency, and visual-motor integration. Educational outcomes included reading and spelling; behavioral outcomes were assessed with the Rutter Parents' Scale and the Premorbid Adjustment Scale (PAS). Adolescent outcome scores were compared among the four groups. A main effect for group was observed for full-scale IQ, Rutter Parents' Scale total scores, and PAS total scores, after controlling for gestational age, socioeconomic status and gender, with the PVH + DIL group showing the most impaired scores compared to the other groups. The current results demonstrate that routine neonatal ultrasound classifications are associated with later cognitive and behavioral outcome. Neonatal ultrasounds could aid in the identification of subgroups of children who are at increased risk of neurodevelopmental problems. These at risk subgroups could then be referred to appropriate early intervention services.

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This study combined high resolution mass spectrometry (HRMS), advanced chemometrics and pathway enrichment analysis to analyse the blood metabolome of patients attending the memory clinic: cases of mild cognitive impairment (MCI; n = 16), cases of MCI who upon subsequent follow-up developed Alzheimer's disease (MCI_AD; n = 19), and healthy age-matched controls (Ctrl; n = 37). Plasma was extracted in acetonitrile and applied to an Acquity UPLC HILIC (1.7μm x 2.1 x 100 mm) column coupled to a Xevo G2 QTof mass spectrometer using a previously optimised method. Data comprising 6751 spectral features were used to build an OPLS-DA statistical model capable of accurately distinguishing Ctrl, MCI and MCI_AD. The model accurately distinguished (R2 = 99.1%; Q2 = 97%) those MCI patients who later went on to develop AD. S-plots were used to shortlist ions of interest which were responsible for explaining the maximum amount of variation between patient groups. Metabolite database searching and pathway enrichment analysis indicated disturbances in 22 biochemical pathways, and excitingly it discovered two interlinked areas of metabolism (polyamine metabolism and L-Arginine metabolism) were differentially disrupted in this well-defined clinical cohort. The optimised untargeted HRMS methods described herein not only demonstrate that it is possible to distinguish these pathologies in human blood but also that MCI patients 'at risk' from AD could be predicted up to 2 years earlier than conventional clinical diagnosis. Blood-based metabolite profiling of plasma from memory clinic patients is a novel and feasible approach in improving MCI and AD diagnosis and, refining clinical trials through better patient stratification.

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Introduction
Mild cognitive impairment (MCI) has clinical value in its ability to predict later dementia. A better understanding of cognitive profiles can further help delineate who is most at risk of conversion to dementia. We aimed to (1) examine to what extent the usual MCI subtyping using core criteria corresponds to empirically defined clusters of patients (latent profile analysis [LPA] of continuous neuropsychological data) and (2) compare the two methods of subtyping memory clinic participants in their prediction of conversion to dementia.

Methods
Memory clinic participants (MCI, n = 139) and age-matched controls (n = 98) were recruited. Participants had a full cognitive assessment, and results were grouped (1) according to traditional MCI subtypes and (2) using LPA. MCI participants were followed over approximately 2 years after their initial assessment to monitor for conversion to dementia.

Results
Groups were well matched for age and education. Controls performed significantly better than MCI participants on all cognitive measures. With the traditional analysis, most MCI participants were in the amnestic multidomain subgroup (46.8%) and this group was most at risk of conversion to dementia (63%). From the LPA, a three-profile solution fit the data best. Profile 3 was the largest group (40.3%), the most cognitively impaired, and most at risk of conversion to dementia (68% of the group).

Discussion
LPA provides a useful adjunct in delineating MCI participants most at risk of conversion to dementia and adds confidence to standard categories of clinical inference.

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Vascular cognitive impairment (VCI), including its severe form, vascular dementia (VaD), is the second most common form of dementia. The genetic etiology of sporadic VCI remains largely unknown. We previously conducted a systematic review and meta-analysis of all published genetic association studies of sporadic VCI prior to 6 July 2012, which demonstrated that APOE (ɛ4, ɛ2) and MTHFR (rs1801133) variants were associated with susceptibility for VCI. De novo genotyping was conducted in a new independent relatively large collaborative European cohort of VaD (nmax = 549) and elderly non-demented samples (nmax = 552). Where available, genotype data derived from Illumina's 610-quad array for 1210 GERAD1 control samples were also included in analyses of genes examined. Associations were tested using the Cochran-Armitage trend test: MTHFR rs1801133 (OR = 1.36, 95% CI 1.16-1.58, p = <0.0001), APOE rs7412 (OR = 0.62, 95% CI 0.42-0.90, p = 0.01), and APOE rs429358 (OR = 1.59, 95% CI 1.17-2.16, p = 0.003). Association was also observed with APOE epsilon alleles; ɛ4 (OR = 1.85, 95% CI 1.35-2.52, p = <0.0001) and ɛ2 (OR = 0.67, 95% CI 0.46-0.98, p = 0.03). Logistic Regression and Bonferroni correction in a subgroup of the cohort adjusted for gender, age, and population maintained the association of APOE rs429358 and ɛ4 allele.