Optimising exposure for children and adolescents with anxiety, OCD and PTSD: a systematic review

Cognitive-behavioural therapy is an effective treatment for anxiety disorders in children and young people, however, many do not benefit. Behavioural exposure appears to be the critical ingredient in the treatment of anxiety disorders. Research with adults has identified innovative strategies to optimise exposure-based treatments, yet it is not clear how to optimise the effects of exposure for children and young people. This review was a preliminary exploration of the association between potential optimisation strategies and treatment procedures and outcomes for the treatment of child anxiety symptoms/disorders. We searched PsychInfo and Medline databases using a systematic search strategy and identified 29 articles. We found preliminary evidence that some specific strategies may enhance the effects of exposure, such as dropping safety behaviours, parents and therapists discouraging avoidance, and the use of homework. However, not one significant finding was replicated by another study for the same time point using the same methodology. To a large degree, this lack of replication reflects a limited number of studies combined with a lack of consistency across studies around conceptualisations, methodological approaches, and outcome measures making it difficult to make meaningful comparisons between studies and draw firm conclusions. Examination is needed of a wide range of theoretically-driven potential optimisation strategies using methodologically robust, preclinical studies with children and young people. Furthermore, the methods used in future research must enable comparisons across studies and explore developmental differences in the effects of particular optimisation strategies

A Hoxb3Mouse Mutant with Abnormal Thoracic Body Wall Development

If the data produced by a digital imaging system is univariate, i.e. if just one scalar measurement (temperature, density, etc.) is made at each pixel, then standard image processing methods for extracting information from this univariate data are well known and relatively simple to apply [1]. Indeed, most of these methods ultimately reduce to information extraction via a visual inspection of an enhanced or restored image of the data displayed in shades of gray or in pseudocolor. What if the imaging system produces multivariate data i.e. what if an array (or vector) of data is measured at each pixel? In this case some information can be extracted with a visual inspection of each image component. However, it is intuitive that such an approach is fundamentally limited because it is univariate and does not account for the inherently high component-to-component correlation typically found in multivariate images. Instead, what is needed is a more comprehensive approach in which the multivariate data is processed in a space whose dimension matches that of the data. Information extraction via a visual inspection of the data can then take place after some arithmetic processing and statistical decisions have been applied to estimate and remove the multivariate correlation and thereby effectively reduce the dimensionality of the data without significantly reducing its information content

Household perceptions of climate change and preferences for mitigation action: the case of the Carbon Pollution Reduction Scheme in Australia

The study aims to reveal Australian households' perceptions of climate change and their preferences for mitigation action. A web-based survey was conducted in November 2008 in which over 600 households from the state of New South Wales were asked for their willingness to bear extra household expenditure to support the 'Carbon Pollution Reduction Scheme', an emissions trading scheme proposed by the Australian government. The results of the study can be summarized in four key findings. First, respondents' willingness to pay for climate change mitigation is significantly influenced by their beliefs of future temperature rise. Support for the policy increased at a decreasing rate as the perceived temperature change rose. Second, perceptions of policy failure have a significant negative impact on respondents' support for the proposed mitigation measure. The higher the perceived likelihood that the measure would not deliver any outcome, the lower was the likelihood that respondents would support the policy. Third, respondent preferences for the proposed policy are influenced by the possibility of reaching a global agreement on emissions reduction. Sample respondents stated significantly higher values for the policy when the biggest polluting countries implement a similar scheme. Finally, respondents' willingness to take action against climate change, both at the national and household level, is found to be influenced by their level of mass-media exposure. Particularly, those respondents who watched 'An Inconvenient Truth' were significantly more likely to act for climate change mitigation than others