The Meaning of Collective Terrorist Threat: Understanding the Subjective Causes of Terrorism Reduces Its Negative Psychological Impact

This article hypothesized that the possibility to construct intellectual meaning of a terrorist attack (i.e., whether participants can cognitively understand why the perpetrators did their crime) reduces the negative psychological consequences typically associated with increased terrorist threat. Concretely, the authors investigated the effect of intellectual meaning (induced by providing additional information about potential economic, cultural, and historical reasons for the terrorist attack) on perceived terrorist threat and associated emotional well-being. Study 1 revealed that pictures of terrorist attacks elicited less experienced terrorist threat when they were presented with background information about the terrorists’ motives (meaning provided) rather than without additional background information (no meaning provided). Study 2 replicated this effect with a different manipulation of terrorist threat (i.e., newspaper article) and clarified the underlying psychological process: Participants in the high terror salience condition with meaning provided experienced less terrorist threat and thus more emotional well-being in the face of crisis than participants in the high terror salience condition without meaning provided. Theoretical and practical implications in the context of psychological health and mass media effects are discussed

Strengths and limitations of microarray-based phenotype prediction: lessons learned from the IMPROVER Diagnostic Signature Challenge

Motivation: After more than a decade since microarrays were used to predict phenotype of biological samples, real-life applications for disease screening and identification of patients who would best benefit from treatment are still emerging. The interest of the scientific community in identifying best approaches to develop such prediction models was reaffirmed in a competition style international collaboration called IMPROVER Diagnostic Signature Challenge whose results we describe herein. Results: Fifty-four teams used public data to develop prediction models in four disease areas including multiple sclerosis, lung cancer, psoriasis and chronic obstructive pulmonary disease, and made predictions on blinded new data that we generated. Teams were scored using three metrics that captured various aspects of the quality of predictions, and best performers were awarded. This article presents the challenge results and introduces to the community the approaches of the best overall three performers, as well as an R package that implements the approach of the best overall team. The analyses of model performance data submitted in the challenge as well as additional simulations that we have performed revealed that (i) the quality of predictions depends more on the disease endpoint than on the particular approaches used in the challenge; (ii) the most important modeling factor (e.g. data preprocessing, feature selection and classifier type) is problem dependent; and (iii) for optimal results datasets and methods have to be carefully matched. Biomedical factors such as the disease severity and confidence in diagnostic were found to be associated with the misclassification rates across the different teams. Availability: The lung cancer dataset is available from Gene Expression Omnibus (accession, GSE43580). The maPredictDSC R package implementing the approach of the best overall team is available at www.bioconductor.org or http://bioinformaticsprb.med.wayne.edu/. Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics onlin

Strengths and limitations of microarray-based phenotype prediction: Lessons learned from the IMPROVER Diagnostic Signature Challenge

ISSN:1367-4803ISSN:1460-205

Verification of systems biology research in the age of collaborative competition.

Collaborative competitions in which communities of researchers compete to solve challenges may facilitate more rigorous scrutiny of scientific results