1,040 research outputs found

    A study of psychiatrists’ concepts of mental illness

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    Background: There are multiple models of mental illness that inform professional and lay understanding. Few studies have formally investigated psychiatrists' attitudes. We aimed to measure how a group of trainee psychiatrists understand familiar mental illnesses in terms of propositions drawn from different models. Method: We used a questionnaire study of a sample of trainees from South London and Maudsley National Health Service (NHS) Foundation Trust designed to assess attitudes across eight models of mental illness (e.g. biological, psychodynamic) and four psychiatric disorders. Methods for analysing repeated measures and a principal components analysis (PCA) were used. Results: No one model was endorsed by all respondents. Model endorsement varied with disorder. Attitudes to schizophrenia were expressed with the greatest conviction across models. Overall, the ‘biological’ model was the most strongly endorsed. The first three components of the PCA (interpreted as dimensions around which psychiatrists, as a group, understand mental illness) accounted for 56% of the variance. Each main component was classified in terms of its distinctive combination of statements from different models: PC1 33% biological versus non-biological; PC2 12% ‘eclectic’ (combining biological, behavioural, cognitive and spiritual models); and PC3 10% psychodynamic versus sociological. Conclusions: Trainee psychiatrists are most committed to the biological model for schizophrenia, but in general are not exclusively committed to any one model. As a group, they organize their attitudes towards mental illness in terms of a biological/non-biological contrast, an ‘eclectic’ view and a psychodynamic/sociological contrast. Better understanding of how professional group membership influences attitudes may facilitate better multidisciplinary working

    Cystic fibrosis: NHLBI workshop on the primary prevention of chronic lung diseases

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    Cystic fibrosis (CF) is a life-limiting, monogenic disorder characterized by chronic sinopulmonary and gastrointestinal involvement. Progressive pulmonary disease leads to death in the majority of patients. Despite its well-defined molecular basis related to defects in the cystic fibrosis transmembrane conductance regulator anion transport channel, there are large gaps in our understanding of the origin of CF lung disease. Disease has been shown to be present in infancy, and there is mounting evidence that abnormalities begin in utero. Heterogeneity of clinical presentations and severity suggest that many factors involved in lung disease have yet to be fully elucidated. Although new advances in therapeutic treatments have shown promise in delaying disease progression, the prevention of pulmonary disease at its origin (primary prevention) should be a key goal of CF care. The objective of this workshop was to (1) review our understanding of the origins of CF lung disease, (2) determine gaps in the knowledge base that are most significant and most likely to enable prevention of CF lung disease, and (3) prioritize new research questions that will promote pulmonary health in both CF and other childhood lung diseases. The goal of this report is to provide recommendations for future research that will improve our understanding of pulmonary development in health and disease, improve outcome measures and biomarkers for early lung disease, and determine therapeutic targets and strategies to prevent the development of lung disease in children with CF

    Detecting the direction of a signal on high-dimensional spheres: Non-null and Le Cam optimality results

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    We consider one of the most important problems in directional statistics, namely the problem of testing the null hypothesis that the spike direction θ\theta of a Fisher-von Mises-Langevin distribution on the pp-dimensional unit hypersphere is equal to a given direction θ0\theta_0. After a reduction through invariance arguments, we derive local asymptotic normality (LAN) results in a general high-dimensional framework where the dimension pnp_n goes to infinity at an arbitrary rate with the sample size nn, and where the concentration κn\kappa_n behaves in a completely free way with nn, which offers a spectrum of problems ranging from arbitrarily easy to arbitrarily challenging ones. We identify various asymptotic regimes, depending on the convergence/divergence properties of (κn)(\kappa_n), that yield different contiguity rates and different limiting experiments. In each regime, we derive Le Cam optimal tests under specified κn\kappa_n and we compute, from the Le Cam third lemma, asymptotic powers of the classical Watson test under contiguous alternatives. We further establish LAN results with respect to both spike direction and concentration, which allows us to discuss optimality also under unspecified κn\kappa_n. To investigate the non-null behavior of the Watson test outside the parametric framework above, we derive its local asymptotic powers through martingale CLTs in the broader, semiparametric, model of rotationally symmetric distributions. A Monte Carlo study shows that the finite-sample behaviors of the various tests remarkably agree with our asymptotic results.Comment: 47 pages, 4 figure

    3D City Models and urban information: Current issues and perspectives

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    Considering sustainable development of cities implies investigating cities in a holistic way taking into account many interrelations between various urban or environmental issues. 3D city models are increasingly used in different cities and countries for an intended wide range of applications beyond mere visualization. Could these 3D City models be used to integrate urban and environmental knowledge? How could they be improved to fulfill such role? We believe that enriching the semantics of current 3D city models, would extend their functionality and usability; therefore, they could serve as integration platforms of the knowledge related to urban and environmental issues allowing a huge and significant improvement of city sustainable management and development. But which elements need to be added to 3D city models? What are the most efficient ways to realize such improvement / enrichment? How to evaluate the usability of these improved 3D city models? These were the questions tackled by the COST Action TU0801 “Semantic enrichment of 3D city models for sustainable urban development”. This book gathers various materials developed all along the four year of the Action and the significant breakthroughs

    The Microbiome in Pediatric Cystic Fibrosis Patients: The Role of Shared Environment Suggests a Window of Intervention

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    Cystic fibrosis (CF) is caused by mutations in the CFTR gene that predispose the airway to infection. Chronic infection by pathogens such as Pseudomonas aeruginosa leads to inflammation that gradually degrades lung function, resulting in morbidity and early mortality. In a previous study of CF monozygotic twins, we demonstrate that genetic modifiers significantly affect the establishment of persistent P. aeruginosa colonization in CF. Recognizing that bacteria other than P. aeruginosa contribute to the CF microbiome and associated pathology, we used deep sequencing of sputum from pediatric monozygotic twins and nontwin siblings with CF to characterize pediatric bacterial communities and the role that genetics plays in their evolution. We found that the microbial communities in sputum from pediatric patients living together were much more alike than those from pediatric individuals living apart, regardless of whether samples were taken from monozygous twins or from nontwin CF siblings living together, which we used as a proxy for dizygous twins. In contrast, adult communities were comparatively monolithic and much less diverse than the microbiome of pediatric patients

    Sources of Variation in Sweat Chloride Measurements in Cystic Fibrosis

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    Rationale: Expanding the use of cystic fibrosis transmembrane conductance regulator (CFTR) potentiators and correctors for the treatment of cystic fibrosis (CF) requires precise and accurate biomarkers. Sweat chloride concentration provides an in vivo assessment of CFTR function, but it is unknown the degree to which CFTR mutations account for sweat chloride variation

    Identifying the mechanisms underpinning recognition of structured sequences of action

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    © 2012 The Experimental Psychology SocietyWe present three experiments to identify the specific information sources that skilled participants use to make recognition judgements when presented with dynamic, structured stimuli. A group of less skilled participants acted as controls. In all experiments, participants were presented with filmed stimuli containing structured action sequences. In a subsequent recognition phase, participants were presented with new and previously seen stimuli and were required to make judgements as to whether or not each sequence had been presented earlier (or were edited versions of earlier sequences). In Experiment 1, skilled participants demonstrated superior sensitivity in recognition when viewing dynamic clips compared with static images and clips where the frames were presented in a nonsequential, randomized manner, implicating the importance of motion information when identifying familiar or unfamiliar sequences. In Experiment 2, we presented normal and mirror-reversed sequences in order to distort access to absolute motion information. Skilled participants demonstrated superior recognition sensitivity, but no significant differences were observed across viewing conditions, leading to the suggestion that skilled participants are more likely to extract relative rather than absolute motion when making such judgements. In Experiment 3, we manipulated relative motion information by occluding several display features for the duration of each film sequence. A significant decrement in performance was reported when centrally located features were occluded compared to those located in more peripheral positions. Findings indicate that skilled participants are particularly sensitive to relative motion information when attempting to identify familiarity in dynamic, visual displays involving interaction between numerous features
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