321 resultados para Cognitive-behavioural


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Objects presented in categorically related contexts are typically named slower than objects presented in unrelated contexts, a phenomenon termed semantic interference. However, not all semantic relationships induce interference. In the present study, we investigated the influence of object part-relations in the blocked cyclic naming paradigm. In Experiment 1 we established that an object's parts do induce a semantic interference effect when named in context compared to unrelated parts (e.g., leaf, root, nut, bark; for tree). In Experiment 2) we replicated the effect during perfusion functional magnetic resonance imaging (fMRI) to identify the cerebral regions involved. The interference effect was associated with significant perfusion signal increases in the hippocampal formation and decreases in the dorsolateral prefrontal cortex. We failed to observe significant perfusion signal changes in the left lateral temporal lobe, a region that shows reliable activity for interference effects induced by categorical relations in the same paradigm and is proposed to mediate lexical-semantic processing. We interpret these results as supporting recent explanations of semantic interference in blocked cyclic naming that implicate working memory mechanisms. However, given the failure to observe significant perfusion signal changes in the left temporal lobe, the results provide only partial support for accounts that assume semantic interference in this paradigm arises solely due to lexical-level processes.

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Extensive research conducted in the occupational stress literature has failed to provide convincing support for the stress-buffering effects of work control on employee adjustment. Drawing on research conducted in the laboratory context, it was proposed that the stress-buffering effects of work control on employee adjustment would be more marked at high, rather than low, levels of self-efficacy. In a sample of 100 customer service representatives, a significant three-way interaction among role conflict, work control and self-efficacy (measured at Time 1) was observed on (low) depersonalization (measured at Time 2). Consistent with expectations, work control reduced the negative effects of work stress on this outcome measure only for employees who perceived high levels of self-efficacy at work. In addition, there was evidence to suggest that self-efficacy moderated the main effects of work control on job satisfaction and somatic health. These findings are discussed in terms of their theoretical contribution to the job strain model, and also in relation to workplace interventions designed to improve levels of employee adjustment.

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This cross-sectional study assessed intellect, cognition, academic function, behaviour, and emotional health of long-term survivors after childhood liver transplantation. Eligible children were >5 yr post-transplant, still attending school, and resident in Queensland. Hearing and neurocognitive testing were performed on 13 transplanted children and six siblings including two twin pairs where one was transplanted and the other not. Median age at testing was 13.08 (range 6.52-16.99) yr; time elapsed after transplant 10.89 (range 5.16-16.37) yr; and age at transplant 1.15 (range 0.38-10.00) yr. Mean full-scale IQ was 97 (81-117) for transplanted children and 105 (87-130) for siblings. No difficulties were identified in intellect, cognition, academic function, and memory and learning in transplanted children or their siblings, although both groups had reduced mathematical ability compared with normal. Transplanted patients had difficulties in executive functioning, particularly in self-regulation, planning and organization, problem-solving, and visual scanning. Thirty-one percent (4/13) of transplanted patients, and no siblings, scored in the clinical range for ADHD. Emotional difficulties were noted in transplanted patients but were not different from their siblings. Long-term liver transplant survivors exhibit difficulties in executive function and are more likely to have ADHD despite relatively intact intellect and cognition.

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This paper describes the development and use of personas, a Human Computer Interaction (HCI) research methodology, within the STIMulate peer learning program, in order to better understand student behaviour patterns and motivations. STIMulate is a support for learning program at the Queensland University of Technology (QUT) in Brisbane, Australia. The program provides assistance in mathematics, science and information technology (IT) for course work students. A STIMulate space is provided for students to study and obtain one-on-one assistance from Peer Learning Facilitators (PLFs), who are experienced students that have excelled in relevant subject areas. This paper describes personas – archetypal users - that represent the motivations and behavioural patterns of students that utilise STIMulate (particularly the IT stream). The personas were developed based on interviews with PLFs, and subsequently validated by a PLF focus group. Seven different personas were developed. The personas enable us to better understand the characteristics of the students utilising the STIMulate program. The research provides a clearer picture of visiting student motivations and behavioural patterns. This has helped us identify gaps in the services provided, and be more aware of our assumptions about students. The personas have been deployed in PLF training programs, to help PLFs provide a better service to the students. The research findings suggest further study on the resonances between some students and PLFs, which we would like to better elicit.

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Within online learning communities, receiving timely and meaningful insights into the quality of learning activities is an important part of an effective educational experience. Commonly adopted methods – such as the Community of Inquiry framework – rely on manual coding of online discussion transcripts, which is a costly and time consuming process. There are several efforts underway to enable the automated classification of online discussion messages using supervised machine learning, which would enable the real-time analysis of interactions occurring within online learning communities. This paper investigates the importance of incorporating features that utilise the structure of on-line discussions for the classification of "cognitive presence" – the central dimension of the Community of Inquiry framework focusing on the quality of students' critical thinking within online learning communities. We implemented a Conditional Random Field classification solution, which incorporates structural features that may be useful in increasing classification performance over other implementations. Our approach leads to an improvement in classification accuracy of 5.8% over current existing techniques when tested on the same dataset, with a precision and recall of 0.630 and 0.504 respectively.

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This paper explores consumer behavioural patterns on a magazine website. By using a unique dataset of real-life click stream data from 295 magazine website visitors, individual sessions are grouped according to the different sections visited on the websites. Interesting behavioural patterns are noted: most importantly, 86 % of all sessions only visit the blogs. This means that the visitors are not exposed to any editorial content at all, and choose to avoid also commercial contents. Sessions visiting editorial content, commercial content or social media links are very few in numbers (each 1 per cent or less of the sessions), thus giving only very limited support to the magazine business model. We noted that consumer behaviour on the magazine website seems to be very goal-oriented and instrumental, rather than exploratory and ritualized. This paper contributes to the current knowledge of media management by shedding light on consumer behaviour on media websites, and opening up the challenges with current media business models. From a more practical perspective, our data questions the general assumption of online platforms as supporter of the print business.

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Background The Global Burden of Disease, Injuries, and Risk Factor study 2013 (GBD 2013) is the first of a series of annual updates of the GBD. Risk factor quantification, particularly of modifiable risk factors, can help to identify emerging threats to population health and opportunities for prevention. The GBD 2013 provides a timely opportunity to update the comparative risk assessment with new data for exposure, relative risks, and evidence on the appropriate counterfactual risk distribution. Methods Attributable deaths, years of life lost, years lived with disability, and disability-adjusted life-years (DALYs) have been estimated for 79 risks or clusters of risks using the GBD 2010 methods. Risk–outcome pairs meeting explicit evidence criteria were assessed for 188 countries for the period 1990–2013 by age and sex using three inputs: risk exposure, relative risks, and the theoretical minimum risk exposure level (TMREL). Risks are organised into a hierarchy with blocks of behavioural, environmental and occupational, and metabolic risks at the first level of the hierarchy. The next level in the hierarchy includes nine clusters of related risks and two individual risks, with more detail provided at levels 3 and 4 of the hierarchy. Compared with GBD 2010, six new risk factors have been added: handwashing practices, occupational exposure to trichloroethylene, childhood wasting, childhood stunting, unsafe sex, and low glomerular filtration rate. For most risks, data for exposure were synthesised with a Bayesian meta-regression method, DisMod-MR 2.0, or spatial-temporal Gaussian process regression. Relative risks were based on meta-regressions of published cohort and intervention studies. Attributable burden for clusters of risks and all risks combined took into account evidence on the mediation of some risks such as high body-mass index (BMI) through other risks such as high systolic blood pressure and high cholesterol. Findings All risks combined account for 57·2% (95% uncertainty interval [UI] 55·8–58·5) of deaths and 41·6% (40·1–43·0) of DALYs. Risks quantified account for 87·9% (86·5–89·3) of cardiovascular disease DALYs, ranging to a low of 0% for neonatal disorders and neglected tropical diseases and malaria. In terms of global DALYs in 2013, six risks or clusters of risks each caused more than 5% of DALYs: dietary risks accounting for 11·3 million deaths and 241·4 million DALYs, high systolic blood pressure for 10·4 million deaths and 208·1 million DALYs, child and maternal malnutrition for 1·7 million deaths and 176·9 million DALYs, tobacco smoke for 6·1 million deaths and 143·5 million DALYs, air pollution for 5·5 million deaths and 141·5 million DALYs, and high BMI for 4·4 million deaths and 134·0 million DALYs. Risk factor patterns vary across regions and countries and with time. In sub-Saharan Africa, the leading risk factors are child and maternal malnutrition, unsafe sex, and unsafe water, sanitation, and handwashing. In women, in nearly all countries in the Americas, north Africa, and the Middle East, and in many other high-income countries, high BMI is the leading risk factor, with high systolic blood pressure as the leading risk in most of Central and Eastern Europe and south and east Asia. For men, high systolic blood pressure or tobacco use are the leading risks in nearly all high-income countries, in north Africa and the Middle East, Europe, and Asia. For men and women, unsafe sex is the leading risk in a corridor from Kenya to South Africa. Interpretation Behavioural, environmental and occupational, and metabolic risks can explain half of global mortality and more than one-third of global DALYs providing many opportunities for prevention. Of the larger risks, the attributable burden of high BMI has increased in the past 23 years. In view of the prominence of behavioural risk factors, behavioural and social science research on interventions for these risks should be strengthened. Many prevention and primary care policy options are available now to act on key risks.

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Dieting and non-dieting are two contrasting approaches to the management of overweight/obesity, but less is known about why people follow non-dieting approaches and how these approaches are associated with health and nutrition status indicators. This thesis enables a greater understanding of why dieting and non-dieting approaches are adopted and provides insight into whether one approach is more favourably associated with nutrition and health status indicators. The findings of this thesis will be useful for clinicians who wish to encourage dieting or non-dieting approaches in their clients and for researchers wishing to understand how best to address overweight and obesity.

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This study describes the results of a controlled clinical trial involving 44 7- to 14-year-old children with recurrent abdominal pain who were randomly allocated to either cognitive-behavioral family intervention (CBFI) or standard pediatric care (SPC). Both treatment conditions resulted in significant improvements on measures of pain intensity and pain behavior. However, the children receiving CBFI had a higher rate of complete elimination of pain, lower levels of relapse at 6- and 12-month follow-up, and lower levels of interference with their activities as a result of pain and parents reported a higher level of satisfaction with the treatment than children receiving SPC. After controlling for pretreatment levels of pain, children's active self-coping and mothers' caregiving strategies were significant independent predictors of pain behavior at posttreatment.

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Sleepiness remains a primary cause of road crashes, the major cause of death in young adults. Light is known to produce a direct alerting effect, but little is known about its effects on sleepy drivers. This study aimed to compare the effect of blue-green light and caffeine on young drivers’ cognitive performance after chronic-partial sleep loss.

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Pharmaceutical Care is defined as “the responsible provision of drug therapy for the purpose of achieving definite outcomes that improve a patient’s quality of life”. One of the fundamental concepts in understanding needs for pharmaceutical care are Drug-Related Problems (DRPs). As the complexity of medication treatment increases, identification of drug-related problems (DRPs) by healthcare professionals remains vital to patient safety and Quality Use of Medicines(QUM). DRPs have been used by many researchers to evaluate the QUM in different settings. DRPs present, however, a list of potential problems not a strategic framework for assessing a medication regimen.

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The growth of APIs and Web services on the Internet, especially through larger enterprise systems increasingly being leveraged for Cloud and software-as-a-service opportuni- ties, poses challenges to improving the efficiency of integration with these services. Interfaces of enterprise systems are typically larger, more complex and overloaded, with single operation having multiple data entities and parameter sets, supporting varying requests, and reflecting versioning across different system releases, compared to fine-grained operations of contemporary interfaces. We propose a technique to support the refactoring of service interfaces by deriving business entities and their relationships. In this paper, we focus on the behavioural aspects of service interfaces, aiming to discover the sequential dependencies of operations (otherwise known as protocol extraction) based on the entities and relationships derived. Specifically, we propose heuristics according to these relationships, and in turn, deriving permissible orders in which operations are invoked. As a result of this, service operations can be refactored on business entity CRUD lines, with explicit behavioural protocols as part of an interface definition. This supports flexible service discovery, composition and integration. A prototypical implementation and analysis of existing Web services, including those of commercial logistic systems (Fedex), are used to validate the algorithms proposed through the paper.

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Doctoral training is strongly focused on honing research skills at the expense of developing teaching competency. As a result, emerging academics are unprepared for the pedagogical requirements of their early-career academic roles. Employing an action research approach, this study investigates the effectiveness of a competency-based teaching development intervention that aims to improve the teaching self-efficacy of doctoral candidates. To conduct this research, we apply the theoretical framework of Cognitive Apprenticeship Theory, a theory of social learning that requires learners to participate in a community of inquiry. Participants report significantly higher levels of teaching self-efficacy and a stronger sense of connectedness to the wider academic community.

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In recent years more and more complex humanoid robots have been developed. On the other hand programming these systems has become more difficult. There is a clear need for such robots to be able to adapt and perform certain tasks autonomously, or even learn by themselves how to act. An important issue to tackle is the closing of the sensorimotor loop. Especially when talking about humanoids the tight integration of perception with actions will allow for improved behaviours, embedding adaptation on the lower-level of the system.

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In this paper, we present the results of an exploratory study that examined the problem of automating content analysis of student online discussion transcripts. We looked at the problem of coding discussion transcripts for the levels of cognitive presence, one of the three main constructs in the Community of Inquiry (CoI) model of distance education. Using Coh-Metrix and LIWC features, together with a set of custom features developed to capture discussion context, we developed a random forest classification system that achieved 70.3% classification accuracy and 0.63 Cohen's kappa, which is significantly higher than values reported in the previous studies. Besides improvement in classification accuracy, the developed system is also less sensitive to overfitting as it uses only 205 classification features, which is around 100 times less features than in similar systems based on bag-of-words features. We also provide an overview of the classification features most indicative of the different phases of cognitive presence that gives an additional insights into the nature of cognitive presence learning cycle. Overall, our results show great potential of the proposed approach, with an added benefit of providing further characterization of the cognitive presence coding scheme.