906 resultados para PTSD, bombing, cognitive models, community, survey


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With the rapid growth of information on the Web, the study of information searching has let to an increased interest. Information behaviour (IB) researchers and information systems (IS) developers are continuously exploring user - Web search interactions to understand and to help users to provide assistance with their information searching. In attempting to develop models of IB, several studies have identified various factors that govern user's information searching and information retrieval (IR), such as age, gender, prior knowledge and task complexity. However, how users' contextual factors, such as cognitive styles, affect Web search interactions has not been clearly explained by the current models of Web Searching and IR. This study explores the influence of users' cognitive styles on their Web search behaviour. The main goal of the study is to enhance Web search models with a better understanding of how these cognitive styles affect Web searching. Modelling Web search behaviour with a greater understanding of user's cognitive styles can help information science researchers and IS designers to bridge the semantic gap between the user and the IS. To achieve the aims of the study, a user study with 50 participants was conducted. The study adopted a mixed method approach incorporating several data collection strategies to gather a range of qualitative and quantitative data. The study utilised pre-search and post-search questionnaires to collect the participants' demographic information and their level of satisfaction about the search interactions. Riding's (1991) Cognitive Style Analysis (CSA) test was used to assess the participants' cognitive styles. Participants completed three predesigned search tasks and the whole user - web search interactions, including thinkaloud, were captured using a monitoring program. Data analysis involved several qualitative and quantitative techniques: the quantitative data gave raise to detailed findings about users' Web searching and cognitive styles, the qualitative data enriched the findings with illustrative examples. The study results provide valuable insights into Web searching behaviour among different cognitive style users. The findings of the study extend our understanding of Web search behaviour and how users search information on the Web. Three key study findings emerged: • Users' Web search behaviour was demonstrated through information searching strategies, Web navigation styles, query reformulation behaviour and information processing approaches while performing Web searches. The manner in which these Web search patterns were demonstrated varied among the users with different cognitive style groups. • Users' cognitive styles influenced their information searching strategies, query reformulation behaviour, Web navigational styles and information processing approaches. Users with particular cognitive styles followed certain Web search patterns. • Fundamental relationships were evident between users' cognitive styles and their Web search behaviours; and these relationships can be illustrated through modelling Web search behaviour. Two models that depict the associations between Web search interactions, user characteristics and users' cognitive styles were developed. These models provide a greater understanding of Web search behaviour from the user perspective, particularly how users' cognitive styles influence their Web search behaviour. The significance of this research is twofold: it will provide insights for information science researchers, information system designers, academics, educators, trainers and librarians who want to better understand how users with different cognitive styles perform information searching on the Web; at the same time, it will provide assistance and support to the users. The major outcomes of this study are 1) a comprehensive analysis of how users search the Web; 2) extensive discussion on the implications of the models developed in this study for future work; and 3) a theoretical framework to bridge high-level search models and cognitive models.

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Cognitive scientists were not quick to embrace the functional neuroimaging technologies that emerged during the late 20th century. In this new century, cognitive scientists continue to question, not unreasonably, the relevance of functional neuroimaging investigations that fail to address questions of interest to cognitive science. However, some ultra-cognitive scientists assert that these experiments can never be of relevance to the study of cognition. Their reasoning reflects an adherence to a functionalist philosophy that arbitrarily and purposefully distinguishes mental information-processing systems from brain or brain-like operations. This article addresses whether data from properly conducted functional neuroimaging studies can inform and subsequently constrain the assumptions of theoretical cognitive models. The article commences with a focus upon the functionalist philosophy espoused by the ultra-cognitive scientists, contrasting it with the materialist philosophy that motivates both cognitive neuroimaging investigations and connectionist modelling of cognitive systems. Connectionism and cognitive neuroimaging share many features, including an emphasis on unified cognitive and neural models of systems that combine localist and distributed representations. The utility of designing cognitive neuroimaging studies to test (primarily) connectionist models of cognitive phenomena is illustrated using data from functional magnetic resonance imaging (fMRI) investigations of language production and episodic memory.

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The high concentration of the world's species in tropical forests endows these systems with particular importance for retaining global biodiversity, yet it also presents significant challenges for ecology and conservation science. The vast number of rare and yet to be discovered species restricts the applicability of species-level modelling for tropical forests, while the capacity of community classification approaches to identify priorities for conservation and management is also limited. Here we assessed the degree to which macroecological modelling can overcome shortfalls in our knowledge of biodiversity in tropical forests and help identify priority areas for their conservation and management. We used 527 plant community survey plots in the Australian Wet Tropics to generate models and predictions of species richness, compositional dissimilarity, and community composition for all the 4,313 vascular plant species recorded across the region (>1.3 million communities (grid cells)). We then applied these predictions to identify areas of tropical forest likely to contain the greatest concentration of species, rare species, endemic species and primitive angiosperm families. Synthesising these alternative attributes of diversity into a single index of conservation value, we identified two areas within the Australian wet tropics that should be a high priority for future conservation actions: the Atherton Tablelands and Daintree rainforest. Our findings demonstrate the value of macroecological modelling in identifying priority areas for conservation and management actions within highly diverse systems, such as tropical forests.

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During the rollout of CGIAR Research Program on Aquatic Agricultural Systems (AAS) in Tonle Sap in 2013, water management was highlighted as one of the key development challenges. With limited capacity to regulate water, the situation oscillates between too much water in the wet season and too little water in the dry season. Access to and availability of water were seen by local communities as major limitations for aquatic and agricultural production, impacting on functions that include the lake fishery, intensive (dry season) rice crops, recession rice, rainfed rice and floating rice by the lakeside. For both fish and rice production, water and water management are determined principally by the natural flooding of the Tonle Sap Lake. This study is based on a community survey on water access, availability and management and was conceived out of the AAS consultation process and was developed to help identify existing practices in water use and management, as well as best practices where lessons can be learned and promising activities scaled out to other communities. The community survey also aims to understand, identify and analyze constraints and opportunities related to water, and includes a gender perspective to better understand the role of women in water management and use.

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The study examined lateral preference in use of hands, feet, eyes, and ears in a group of nearly 5000 schoolchildren in Northern Ireland. Performance tests were carried out by student teachers during their school-based work in 2002 and data were submitted on-line. Six tasks were used-writing, throwing a ball, kicking a ball, hopping, listening to quiet sounds, and looking through a cardboard tube. There was right bias in every task but the extent of it differed between tasks. Males were generally less right biased than females, and younger children less than older ones; for hearing, the changes with age were markedly different in the two sexes, with females showing a strong increase in right bias but males showing none. These observational results do little to illuminate the reasons for the patterns observed.

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Two concepts that have captured the imagination of the educational community in the last 60 years have been those of ‘reflective practice’ and ‘action research’. Both, in their various forms, are considered to be critical dimensions of the professional development of teachers. However, whilst both were receiving academic attention during the 1930s and 1940s (Lewin, 1934, cited in Adelman, 1993; Lewin, 1946; Dewey, 1933), it was not until Stenhouse’s (1975) notion of the teacher-as-researcher that the two came most compellingly into relationship and educational action research as a process, which held at its centre different kinds of reflection, began to be reformulated in Britain (Carr, 1993). This article considers the important part played in teachers’ development by different kinds of action research. Its central thesis is that, although action research has a critical role to play not least as a means of building the capacity of teachers as researchers of their own practice, there has been insufficient attention given to both the nature of reflection in the action research process, and its relationship to the purposes, processes and outcomes. The article challenges the rational, cognitive models of reflection that are implicit in much of the action research literature. It suggests that more attention needs to be given to the importance of the role of emotion in understanding and developing the capacities for reflection which facilitates personal, professional and ultimately system change.

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Cognitive models of posttraumatic stress disorder (PTSD) assert that memory processes play a significant role in PTSD (see e.g., Ehlers & Clark, 2000). Intrusive reexperiencing in PTSD has been linked to perceptual processing of trauma-related material with a corresponding hypothesized lack of conceptual processing. In an experimental study that included clinical participants with and without PTSD (N = 50), perceptual priming and conceptual priming for trauma-related, general threat, and neutral words were investigated in a population with chronic trauma-induced complaints as a result of the Troubles in Northern Ireland. The study used a new version of the word-stem completion task (Michael, Ehlers, & Halligan, 2005) and a word-cue association task. It also assessed the role of dissociation in threat processing. Further evidence of enhanced perceptual priming in PTSD for trauma stimuli was found, along with evidence of lack of conceptual priming for such stimuli. Furthermore, this pattern of priming for trauma-related words was associated with PTSD severity, and state dissociation and PTSD group made significant contributions to predicting perceptual priming for trauma words. The findings shed light on the importance of state dissociation in trauma-related information processing and posttraumatic symptoms.

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Objective
To assess the extent and nature of psychiatric morbidity among children (aged 8 to 13 years) 15 months after a car bomb explosion in the town of Omagh, Northern Ireland.

Method
A survey was conducted of 1945 school children attending 13 schools in the Omagh district. Questionnaires included demographic details, measures of exposure, the Horowitz Impact of Events Scale, the Birleson Self-Rating Depression Scale, and the Spence Children’s Anxiety Scale.

Results
Children directly exposed to the bomb reported higher levels of probable PTSD (70%), and psychological distress than those not exposed. Direct exposure was more closely associated with an increase in PTSD symptoms than in general psychiatric distress. Significant predictors of increased IES scores included being male, witnessing people injured and reporting a perceived life threat but when co-morbid anxiety and depression are included as potential predictors anxiety remains the only significant predictor of PTSD scores.

Conclusions
School-based studies are a potentially valuable means of screening and assessing for PTSD in children after large-scale tragedies. Assessment should consider type of exposure, perceived life threat and other co-morbid anxiety as risk factors for PTSD.

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Background and objectives: Cognitive models suggest that attentional biases are integral in the maintenance of obsessive-compulsive symptoms (OCS). Such biases have been established experimentally in anxiety disorders; however, the evidence is unclear in Obsessive Compulsive disorder (OCD). In the present study, an eye-tracking methodology was employed to explore attentional biases in relation to OCS.
Methods: A convenience sample of 85 community volunteers was assessed on OCS using the Yale-Brown Obsessive Compulsive Scale-self report. Participants completed an eye-tracking paradigm where they were exposed to OCD, Aversive and Neutral visual stimuli. Indices of attentional bias were derived from the eye-tracking data.
Results: Simple linear regressions were performed with OCS severity as the predictor and eye-tracking measures of the different attentional biases for each of the three stimuli types were the criterion variables. Findings revealed that OCS severity moderately predicted greater frequency and duration of fixations on OCD stimuli, which reflect the maintenance attentional bias. No significant results were found in support of other biases.
Limitations: Interpretations based on a non-clinical sample limit the generalisability of the conclusions, although use of such samples in OCD research has been found to be comparable to clinical populations. Future research would include both clinical and sub-clinical participants.
Conclusions: Results provide some support for the theory of maintained attention in OCD attentional biases, as opposed to vigilance theory. Individuals with greater OCS do not orient to OCD stimuli any faster than individuals with lower OCS, but once a threat is identified, these individuals allocate more attention to OCS-relevant stimuli.

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Background: Biases in the interpretation of ambiguous material are central to cognitive models of anxiety; however, understanding of the association between interpretation and anxiety in childhood is limited. To address this, a prospective investigation of the stability and specificity of anxious cognitions and anxiety and the relationship between these factors was conducted. Method: Sixty-five children (10–11 years) from a community sample completed measures of self-reported anxiety, depression, and conduct problems, and responded to ambiguous stories at three time points over one-year. Results: Individual differences in biases in interpretation of ambiguity (specifically “anticipated distress” and “threat interpretation”) were stable over time. Furthermore, anticipated distress and threat interpretation were specifically associated with anxiety symptoms. Distress anticipation predicted change in anxiety symptoms over time. In contrast, anxiety scores predicted change in threat interpretation over time. Conclusions: The results suggest that different cognitive constructs may show different longitudinal links with anxiety. These preliminary findings extend research and theory on anxious cognitions and their link with anxiety in children, and suggest that these cognitive processes may be valuable targets for assessment and intervention.

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The extent to which cognitive models of development and maintenance of depression apply to adolescents is largely untested, despite the widespread application of Cognitive Behavior Therapy (CBT) for depressed adolescents. Cognitive models suggest that negative cognitions, including interpretation bias, play a role in etiology and maintenance of depression. Given that cognitive development is incomplete by the teenage years and that CBT is not superior to non-cognitive treatments in the treatment of adolescent depression, it is important to test the underlying model. The primary aim of this study was to test the hypothesis that interpretation biases are exhibited by depressed adolescents. Four groups of adolescents were recruited: clinically-referred depressed (n = 27), clinically-referred non-depressed (n = 24), community with elevated depression symptoms (n = 42) and healthy community (n = 150). Participants completed a 20 item ambiguous scenarios questionnaire. Clinically-referred depressed adolescents made significantly more negative interpretations and rated scenarios as less pleasant than all other groups. The results suggest that this element of the cognitive model of depression is applicable to adolescents. Other aspects of the model should be tested so that cognitive treatment can be modified or adapted if necessary.

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Background: A number of cognitive appraisals have been identified as important in the manifestation of obsessive-compulsive disorder (OCD) in adults. There have, however, been few attempts to explore these cognitive appraisals in clinical groups of young people. Method: This study compared young people aged between 11 and 18 years with OCD (N ¼ 28), young people with other types of anxiety disorders (N ¼ 28) and a non-clinical group (N ¼ 62) on three questionnaire measures of cognitive appraisals. These were inflated responsibility (Responsibility Attitude Scale; Salkovskis et al., 2000), thought–action fusion – likelihood other (Thought–Action Fusion Scale; Shafran, Thordarson & Rachman, 1996) and perfectionism (Multidimensional Perfectionism Scale; Frost, Marten, Luhart & Rosenblate, 1990). Results: The young people with OCD had significantly higher scores on inflated responsibility, thought–action fusion – (likelihood other), and one aspect of perfectionism, concern over mistakes, than the other groups. In addition, inflated responsibility independently predicted OCD symptom severity. Conclusions: The results generally support a downward extension of the cognitive appraisals held by adults with OCD to young people with the disorder. Some of the results, however, raise issues about potential developmental shifts in cognitive appraisals. The findings are discussed in relation to implications for the cognitive model of OCD and cognitive behavioural therapy for young people with OCD. Keywords: Cognitive models, inflated responsibility, obsessive-compulsive disorder, perfectionism, thought–action fusion. Abbreviations: ADIS-C: Anxiety Disorders Interview Schedule for Children; ADIS-P: Anxiety Disorders Interview Schedule for Parents; E/RP: Exposure/Response Prevention; LOI-CV: Leyton Obsessional Inventory – Child Version; MPS: Multidimensional Perfectionism Scale; OCD: Obsessive-Compulsive Disorder; RAS: Responsibility Attitude Scale; TAF-LO: Thought–Action Fusion – (Likelihood Other).

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Differences-in-Differences (DID) is one of the most widely used identification strategies in applied economics. However, how to draw inferences in DID models when there are few treated groups remains an open question. We show that the usual inference methods used in DID models might not perform well when there are few treated groups and errors are heteroskedastic. In particular, we show that when there is variation in the number of observations per group, inference methods designed to work when there are few treated groups tend to (under-) over-reject the null hypothesis when the treated groups are (large) small relative to the control groups. This happens because larger groups tend to have lower variance, generating heteroskedasticity in the group x time aggregate DID model. We provide evidence from Monte Carlo simulations and from placebo DID regressions with the American Community Survey (ACS) and the Current Population Survey (CPS) datasets to show that this problem is relevant even in datasets with large numbers of observations per group. We then derive an alternative inference method that provides accurate hypothesis testing in situations where there are few treated groups (or even just one) and many control groups in the presence of heteroskedasticity. Our method assumes that we can model the heteroskedasticity of a linear combination of the errors. We show that this assumption can be satisfied without imposing strong assumptions on the errors in common DID applications. With many pre-treatment periods, we show that this assumption can be relaxed. Instead, we provide an alternative inference method that relies on strict stationarity and ergodicity of the time series. Finally, we consider two recent alternatives to DID when there are many pre-treatment periods. We extend our inference methods to linear factor models when there are few treated groups. We also derive conditions under which a permutation test for the synthetic control estimator proposed by Abadie et al. (2010) is robust to heteroskedasticity and propose a modification on the test statistic that provided a better heteroskedasticity correction in our simulations.

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Differences-in-Differences (DID) is one of the most widely used identification strategies in applied economics. However, how to draw inferences in DID models when there are few treated groups remains an open question. We show that the usual inference methods used in DID models might not perform well when there are few treated groups and errors are heteroskedastic. In particular, we show that when there is variation in the number of observations per group, inference methods designed to work when there are few treated groups tend to (under-) over-reject the null hypothesis when the treated groups are (large) small relative to the control groups. This happens because larger groups tend to have lower variance, generating heteroskedasticity in the group x time aggregate DID model. We provide evidence from Monte Carlo simulations and from placebo DID regressions with the American Community Survey (ACS) and the Current Population Survey (CPS) datasets to show that this problem is relevant even in datasets with large numbers of observations per group. We then derive an alternative inference method that provides accurate hypothesis testing in situations where there are few treated groups (or even just one) and many control groups in the presence of heteroskedasticity. Our method assumes that we know how the heteroskedasticity is generated, which is the case when it is generated by variation in the number of observations per group. With many pre-treatment periods, we show that this assumption can be relaxed. Instead, we provide an alternative application of our method that relies on assumptions about stationarity and convergence of the moments of the time series. Finally, we consider two recent alternatives to DID when there are many pre-treatment groups. We extend our inference method to linear factor models when there are few treated groups. We also propose a permutation test for the synthetic control estimator that provided a better heteroskedasticity correction in our simulations than the test suggested by Abadie et al. (2010).

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Bioequivalence trials are abbreviated clinical trials whereby a generic drug or new formulation is evaluated to determine if it is "equivalent" to a corresponding previously approved brand-name drug or formulation. In this manuscript, we survey the process of testing bioequivalence and advocate the likelihood paradigm for representing the resulting data as evidence. We emphasize the unique conflicts between hypothesis testing and confidence intervals in this area - which we believe are indicative of the existence of the systemic defects in the frequentist approach - that the likelihood paradigm avoids. We suggest the direct use of profile likelihoods for evaluating bioequivalence and examine the main properties of profile likelihoods and estimated likelihoods under simulation. This simulation study shows that profile likelihoods are a reasonable alternative to the (unknown) true likelihood for a range of parameters commensurate with bioequivalence research. Our study also shows that the standard methods in the current practice of bioequivalence trials offers only weak evidence from the evidential point of view.