How well do the theory of reasoned action and theory of planned behaviour predict intentions and attendance at screening programmes? A meta-analysis

Meta-analysis was used to quantify how well the Theories of Reasoned Action and Planned Behaviour have predicted intentions to attend screening programmes and actual attendance behaviour. Systematic literature searches identified 33 studies that were included in the review. Across the studies as a whole, attitudes had a large-sized relationship with intention, while subjective norms and perceived behavioural control (PBC) possessed medium-sized relationships with intention. Intention had a medium-sized relationship with attendance, whereas the PBC-attendance relationship was small sized. Due to heterogeneity in results between studies, moderator analyses were conducted. The moderator variables were (a) type of screening test, (b) location of recruitment, (c) screening cost and (d) invitation to screen. All moderators affected theory of planned behaviour relationships. Suggestions for future research emerging from these results include targeting attitudes to promote intention to screen, a greater use of implementation intentions in screening information and examining the credibility of different screening providers

A Computational Approach to Analyze the Mechanism of Action of the Kinase Inhibitor Bafetinib

Prediction of drug action in human cells is a major challenge in biomedical research. Additionally, there is strong interest in finding new applications for approved drugs and identifying potential side effects. We present a computational strategy to predict mechanisms, risks and potential new domains of drug treatment on the basis of target profiles acquired through chemical proteomics. Functional protein-protein interaction networks that share one biological function are constructed and their crosstalk with the drug is scored regarding function disruption. We apply this procedure to the target profile of the second-generation BCR-ABL inhibitor bafetinib which is in development for the treatment of imatinib-resistant chronic myeloid leukemia. Beside the well known effect on apoptosis, we propose potential treatment of lung cancer and IGF1R expressing blast crisis

Evaluating everyday explanations

People frequently rely on explanations provided by others to understand complex phenomena. A fair amount of attention has been devoted to the study of scientific explanation, and less on understanding how people evaluate naturalistic, everyday explanations. Using a corpus of diverse explanations from Reddit's "Explain Like I'm Five" and other online sources, we assessed how well a variety of explanatory criteria predict judgments of explanation quality. We find that while some criteria previously identified as explanatory virtues do predict explanation quality in naturalistic settings, other criteria, such as simplicity, do not. Notably, we find that people have a preference for complex explanations that invoke more causal mechanisms to explain an effect. We propose that this preference for complexity is driven by a desire to identify enough causes to make the effect seem inevitable