Writing impact case studies: a comparative study of high-scoring and low-scoring case studies from REF2014

This paper reports on two studies that used qualitative thematic and quantitative linguistic analysis, respectively, to assess the content and language of the largest ever sample of graded research impact case studies, from the UK Research Excellence Framework 2014 (REF). The paper provides the first empirical evidence across disciplinary main panels of statistically significant linguistic differences between high- versus low-scoring case studies, suggesting that implicit rules linked to written style may have contributed to scores alongside the published criteria on the significance, reach and attribution of impact. High-scoring case studies were more likely to provide specific and high-magnitude articulations of significance and reach than low-scoring cases. High-scoring case studies contained attributional phrases which were more likely to attribute research and/or pathways to impact, and they were written more coherently (containing more explicit causal connections between ideas and more logical connectives) than low-scoring cases. High-scoring case studies appear to have conformed to a distinctive new genre of writing, which was clear and direct, and often simplified in its representation of causality between research and impact, and less likely to contain expressions of uncertainty than typically associated with academic writing. High-scoring case studies in two Main Panels were significantly easier to read than low-scoring cases on the Flesch Reading Ease measure, although both high-scoring and low-scoring cases tended to be of “graduate” reading difficulty. The findings of our work enable impact case study authors to better understand the genre and make content and language choices that communicate their impact as effectively as possible. While directly relevant to the assessment of impact in the UK’s Research Excellence Framework, the work also provides insights of relevance to institutions internationally who are designing evaluation frameworks for research impact

Sustaining remission of psychotic depression: Rationale, design and methodology of STOP-PD II

Background: Psychotic depression (PD) is a severe disabling disorder with considerable morbidity and mortality. Electroconvulsive therapy and pharmacotherapy are each efficacious in the treatment of PD. Expert guidelines recommend the combination of antidepressant and antipsychotic medications in the acute pharmacologic treatment of PD. However, little is known about the continuation treatment of PD. Of particular concern, it is not known whether antipsychotic medication needs to be continued once an episode of PD responds to pharmacotherapy. This issue has profound clinical importance. On the one hand, the unnecessary continuation of antipsychotic medication exposes a patient to adverse effects, such as weight gain and metabolic disturbance. On the other hand, premature discontinuation of antipsychotic medication has the potential risk of early relapse of a severe disorder.Methods/design: The primary goal of this multicenter randomized placebo-controlled trial is to assess the risks and benefits of continuing antipsychotic medication in persons with PD once the episode of depression has responded to treatment with an antidepressant and an antipsychotic. Secondary goals are to examine age and genetic polymorphisms as predictors or moderators of treatment variability, potentially leading to more personalized treatment of PD. Individuals aged 18-85 years with unipolar psychotic depression receive up to 12 weeks of open-label treatment with sertraline and olanzapine. Participants who achieve remission of psychosis and remission/near-remission of depressive symptoms continue with 8 weeks of open-label treatment to ensure stability of remission. Participants with stability of remission are then randomized to 36 weeks of double-blind treatment with either sertraline and olanzapine or sertraline and placebo. Relapse is the primary outcome. Metabolic changes are a secondary outcome.Discussion: This trial will provide clinicians with much-needed evidence to guide the continuation and maintenance treatment of one of the most disabling and lethal of psychiatric disorders.Trial registration and URL: NCT: NCT01427608. © 2013 Flint et al; licensee BioMed Central Ltd

Genome-wide association studies of cancer: current insights and future perspectives.

Genome-wide association studies (GWAS) provide an agnostic approach for investigating the genetic basis of complex diseases. In oncology, GWAS of nearly all common malignancies have been performed, and over 450 genetic variants associated with increased risks have been identified. As well as revealing novel pathways important in carcinogenesis, these studies have shown that common genetic variation contributes substantially to the heritable risk of many common cancers. The clinical application of GWAS is starting to provide opportunities for drug discovery and repositioning as well as for cancer prevention. However, deciphering the functional and biological basis of associations is challenging and is in part a barrier to fully unlocking the potential of GWAS

Interaction of first-order and isodipole statistics in a texture segregation task

Image statistics are often classified as first-order (e.g., luminance), second-order (e.g., contrast, autocorrelation, power spectrum) and high-order (e.g., fourth-order isodipole). Many studies of visual texture processing have considered texture discrimination based on one kind of image statistic, but few have examined how these statistics interact. To examine the interaction of isodipole statistics and luminance statistics, we construct a novel two-dimensional space of binary textures. One axis in this space, gamma, specifies the bias in luminance statistics (gamma= 1 for all white, 0 for a 50:50 mix, -1 for all black). The second axis, alpha, specifies the bias in local fourth-order statistics (alpha=1 for the "even" texture, -1 for the " odd" texture). Long-range statistics and statistics of other orders are determined by maximizing entropy. This uniquely defines the textures in terms of alpha and gamma (within a defined range), and thus generates a two-parameter perceptual space. We examined the ability of subjects (N=2) to segregate textures with specified structure (alpha and/or gamma nonzero) from a fully random texture (alpha=0, gamma=0) in a 4-AFC paradigm. For subject CC, similar Weibull functions (shape parameter 2) provided good fits to the data along the luminance and fourth-order axes in this space. Sensitivity along the luminance axis was approximately four times the sensitivity along the fourth-order axis. For subject MC, sensitivities to the two statistics were in similar ratio, but Weibull functions along the fourth-order (alpha) axis were substantially steeper (shape parameter 4) than along the luminance (gamma) axis (shape parameter of 2). Along oblique directions, performance of both subjects was significantly less than predicted by probability summation. For subject CC but not MC, performance was also significantly less than predicted by a Euclidean geometry within this texture space