Cognitive-behavioral therapy for obsessive-compulsive disorder: access to treatment, prediction of long-term outcome with neuroimaging.

This article reviews issues related to a major challenge to the field for obsessive-compulsive disorder (OCD): improving access to cognitive-behavioral therapy (CBT). Patient-related barriers to access include the stigma of OCD and reluctance to take on the demands of CBT. Patient-external factors include the shortage of trained CBT therapists and the high costs of CBT. The second half of the review focuses on one partial, yet plausible aid to improve access - prediction of long-term response to CBT, particularly using neuroimaging methods. Recent pilot data are presented revealing a potential for pretreatment resting-state functional magnetic resonance imaging and magnetic resonance spectroscopy of the brain to forecast OCD symptom severity up to 1 year after completing CBT

Improved processing of microarray data using image reconstruction techniques

Spotted cDNA microarray data analysis suffers from various problems such as noise from a variety of sources, missing data, inconsistency, and, of course, the presence of outliers. This paper introduces a new method that dramatically reduces the noise when processing the original image data. The proposed approach recreates the microarray slide image, as it would have been with all the genes removed. By subtracting this background recreation from the original, the gene ratios can be calculated with more precision and less influence from outliers and other artifacts that would normally make the analysis of this data more difficult. The new technique is also beneficial, as it does not rely on the accurate fitting of a region to each gene, with its only requirement being an approximate coordinate. In experiments conducted, the new method was tested against one of the mainstream methods of processing spotted microarray images. Our method is shown to produce much less variation in gene measurements. This evidence is supported by clustering results that show a marked improvement in accuracy

The Consequences of Non-Classical Measurement Error for Distributional Analysis

This paper analyzes the consequences of non-classical measurement error for distributional analysis. We show that for a popular set of distributions negative correlation between the measurement error (u) and the true value (y) may reduce the bias in the estimated distribution at every value of y. For other distributions the impact of non-classical measurement di¤ers throughout the support of the distribution. We illustrate the practical importance of these results using models of unemployment duration and income.Distribution functions,Non-classical measurement error,

Theology at the coal-face of hospitalisation - the development and evaluation of a postgraduate certificate in Healthcare Chaplaincy

Healthcare chaplaincy is working towards recognition as a registered health profession. An accredited programme of professional education is part of that process. The University of Glasgow supported by NHS Education for Scotland have developed a programme of professional education for healthcare chaplains that is integrated into an MSc. (MedSci) in healthcare. This article outlines the commissioning, development and evaluation of a postgraduate certificate in healthcare chaplaincy by students, clinical mentors and experienced healthcare chaplains. It also highlights an innovative approach to practice development in spiritual and religious care in healthcare