The Screening Scale for Pedophilic Interests (SSPI): Construct, Predictive, and Incremental Validity

This study of 410 adult male sex offenders against children, using data from the Dynamic Supervision Project (Hanson, Harris, Scott, & Helmus, 2007), examined the construct, predictive, and incremental validity of the Screening Scale for Pedophilic Interests (SSPI; Seto & Lalumière, 2001), a brief proxy measure of phallometrically assessed sexual response to children that is based on sexual victim characteristics. As predicted, the SSPI was significantly related to the Deviant Sexual Interests item on the STABLE-2007 (Hanson et al., 2007), a dynamic risk measure encompassing multiple domains, and with the Deviant Sexual Interests item from its predecessor, the STABLE-2000 (Hanson et al., 2007). The SSPI was unrelated (or more weakly related) to items measuring general antisociality. In addition, the SSPI significantly predicted sexual recidivism, defined as new charges or convictions for sexual offenses, and a broader sexual recidivism outcome that included breaches of community supervision conditions that might involve sexually motivated behavior (e.g., being in the presence of children unsupervised). The SSPI did not add to the predictive accuracy of 2 actuarial risk measures, the Static-99R and Static-200R (Helmus, Thornton, Hanson, & Babchishin, 2012), but it did add to the predictive accuracy of the STABLE-2007. Additional analyses suggest the SSPI can serve as a substitute for the STABLE-2007 Deviant Sexual Interests item, if necessary (e.g., in archival research), when assessing sexual offenders against children

Spanish validation of Bad Sobernheim Stress Questionnaire (BSSQ (brace).es) for adolescents with braces

<p>Abstract</p> <p>Background</p> <p>As a result of scientific and medical professionals gaining interest in Stress and Health Related Quality of Life (HRQL), the aim of our research is, thus, to validate into Spanish the German questionnaire <b>Bad Sobernheim Stress Questionnaire (BSSQ) (mit Korsett)</b>, for adolescents wearing braces.</p> <p>Methods</p> <p>The methodology used adheres to literature on trans-cultural adaptation by doing a translation and a back translation; it involved 35 adolescents, ages ranging between 10 and 16, with Adolescent Idiopathic Scoliosis (AIS) and wearing the same kind of brace (Rigo System Chêneau Brace). The materials used were a socio-demographics data questionnaire, the SRS-22 and the Spanish version of BSSQ(brace).es. The statistical analysis calculated the reliability (test-retest reliability and internal consistency) and the validity (convergent and construct validity) of the BSSQ (brace).es.</p> <p>Results</p> <p>BSSQ(brace).es is reliable because of its satisfactory internal consistency (Cronbach's alpha coefficient was 0.809, p < 0.001) and temporal stability (test-retest method with a Pearson correlation coefficient of 0.902 (p < 0.01)).</p> <p>It demonstrated convergent validity with SRS-22 since the Pearson correlation coefficient was 0.656 (p < 0.01). By undertaking an Exploratory Principal Components Analysis, a latent structure was found based on two Components which explicate the variance at 60.8%.</p> <p>Conclusions</p> <p>BSSQ (brace).es is reliable and valid and can be used with Spanish adolescents to assess the stress level caused by the brace.</p

The metaRbolomics Toolbox in Bioconductor and beyond

Metabolomics aims to measure and characterise the complex composition of metabolites in a biological system. Metabolomics studies involve sophisticated analytical techniques such as mass spectrometry and nuclear magnetic resonance spectroscopy, and generate large amounts of high-dimensional and complex experimental data. Open source processing and analysis tools are of major interest in light of innovative, open and reproducible science. The scientific community has developed a wide range of open source software, providing freely available advanced processing and analysis approaches. The programming and statistics environment R has emerged as one of the most popular environments to process and analyse Metabolomics datasets. A major benefit of such an environment is the possibility of connecting different tools into more complex workflows. Combining reusable data processing R scripts with the experimental data thus allows for open, reproducible research. This review provides an extensive overview of existing packages in R for different steps in a typical computational metabolomics workflow, including data processing, biostatistics, metabolite annotation and identification, and biochemical network and pathway analysis. Multifunctional workflows, possible user interfaces and integration into workflow management systems are also reviewed. In total, this review summarises more than two hundred metabolomics specific packages primarily available on CRAN, Bioconductor and GitHub

Bioclipse: an open source workbench for chemo- and bioinformatics

BACKGROUND: There is a need for software applications that provide users with a complete and extensible toolkit for chemo- and bioinformatics accessible from a single workbench. Commercial packages are expensive and closed source, hence they do not allow end users to modify algorithms and add custom functionality. Existing open source projects are more focused on providing a framework for integrating existing, separately installed bioinformatics packages, rather than providing user-friendly interfaces. No open source chemoinformatics workbench has previously been published, and no sucessful attempts have been made to integrate chemo- and bioinformatics into a single framework. RESULTS: Bioclipse is an advanced workbench for resources in chemo- and bioinformatics, such as molecules, proteins, sequences, spectra, and scripts. It provides 2D-editing, 3D-visualization, file format conversion, calculation of chemical properties, and much more; all fully integrated into a user-friendly desktop application. Editing supports standard functions such as cut and paste, drag and drop, and undo/redo. Bioclipse is written in Java and based on the Eclipse Rich Client Platform with a state-of-the-art plugin architecture. This gives Bioclipse an advantage over other systems as it can easily be extended with functionality in any desired direction. CONCLUSION: Bioclipse is a powerful workbench for bio- and chemoinformatics as well as an advanced integration platform. The rich functionality, intuitive user interface, and powerful plugin architecture make Bioclipse the most advanced and user-friendly open source workbench for chemo- and bioinformatics. Bioclipse is released under Eclipse Public License (EPL), an open source license which sets no constraints on external plugin licensing; it is totally open for both open source plugins as well as commercial ones. Bioclipse is freely available at

Standardized NEON organismal data for biodiversity research

Understanding patterns and drivers of species distribution and abundance, and thus biodiversity, is a core goal of ecology. Despite advances in recent decades, research into these patterns and processes is currently limited by a lack of standardized, high-quality, empirical data that span large spatial scales and long time periods. The NEON fills this gap by providing freely available observational data that are generated during robust and consistent organismal sampling of several sentinel taxonomic groups within 81 sites distributed across the United States and will be collected for at least 30 years. The breadth and scope of these data provide a unique resource for advancing biodiversity research. To maximize the potential of this opportunity, however, it is critical that NEON data be maximally accessible and easily integrated into investigators\u27 workflows and analyses. To facilitate its use for biodiversity research and synthesis, we created a workflow to process and format NEON organismal data into the ecocomDP (ecological community data design pattern) format that were available through the ecocomDP R package; we then provided the standardized data as an R data package (neonDivData). We briefly summarize sampling designs and data wrangling decisions for the major taxonomic groups included in this effort. Our workflows are open-source so the biodiversity community may: add additional taxonomic groups; modify the workflow to produce datasets appropriate for their own analytical needs; and regularly update the data packages as more observations become available. Finally, we provide two simple examples of how the standardized data may be used for biodiversity research. By providing a standardized data package, we hope to enhance the utility of NEON organismal data in advancing biodiversity research and encourage the use of the harmonized ecocomDP data design pattern for community ecology data from other ecological observatory networks