Peer rejection and social information-processing factors in the development of aggressive behavior problems in children.

The relation between social rejection and growth in antisocial behavior was investigated. In Study 1,259 boys and girls (34% African American) were followed from Grades 1 to 3 (ages 6-8 years) to Grades 5 to 7 (ages 10-12 years). Early peer rejection predicted growth in aggression. In Study 2,585 boys and girls (16% African American) were followed from kindergarten to Grade 3 (ages 5-8 years), and findings were replicated. Furthermore, early aggression moderated the effect of rejection, such that rejection exacerbated antisocial development only among children initially disposed toward aggression. In Study 3, social information-processing patterns measured in Study 1 were found to mediate partially the effect of early rejection on later aggression. In Study 4, processing patterns measured in Study 2 replicated the mediation effect. Findings are integrated into a recursive model of antisocial development.

Bayesian inference of the number of factors in gene-expression analysis: application to human virus challenge studies.

BACKGROUND: Nonparametric Bayesian techniques have been developed recently to extend the sophistication of factor models, allowing one to infer the number of appropriate factors from the observed data. We consider such techniques for sparse factor analysis, with application to gene-expression data from three virus challenge studies. Particular attention is placed on employing the Beta Process (BP), the Indian Buffet Process (IBP), and related sparseness-promoting techniques to infer a proper number of factors. The posterior density function on the model parameters is computed using Gibbs sampling and variational Bayesian (VB) analysis. RESULTS: Time-evolving gene-expression data are considered for respiratory syncytial virus (RSV), Rhino virus, and influenza, using blood samples from healthy human subjects. These data were acquired in three challenge studies, each executed after receiving institutional review board (IRB) approval from Duke University. Comparisons are made between several alternative means of per-forming nonparametric factor analysis on these data, with comparisons as well to sparse-PCA and Penalized Matrix Decomposition (PMD), closely related non-Bayesian approaches. CONCLUSIONS: Applying the Beta Process to the factor scores, or to the singular values of a pseudo-SVD construction, the proposed algorithms infer the number of factors in gene-expression data. For real data the "true" number of factors is unknown; in our simulations we consider a range of noise variances, and the proposed Bayesian models inferred the number of factors accurately relative to other methods in the literature, such as sparse-PCA and PMD. We have also identified a "pan-viral" factor of importance for each of the three viruses considered in this study. We have identified a set of genes associated with this pan-viral factor, of interest for early detection of such viruses based upon the host response, as quantified via gene-expression data.

Age Effects in Cultural Life Scripts.

Life scripts are culturally shared expectations about the timing of life events in an idealized life course. Because they are cultural semantic knowledge, they should be known by all adult age groups including those who have not lived through all events in the life script, but this has not been tested previously. Young, middle-aged and older adults from the Netherlands were therefore asked in this online study to imagine an ordinary Dutch infant and to name the seven most important events that were likely to take place in the life of this prototypical child. Participants subsequently answered questions about at what ages these events were expected to occur and about their prevalence, importance and valence. We found that the cultural life script was similar for young, middle-aged and older adults and for adults with different educational attainment.

Text-messaging as a Tool for Medication Adherence and Behavior Change in Disease Management among Patients with Coronary Heart Disease

Background: Evidence-based medication and lifestyle modification are important for secondary prevention of cardiovascular disease but are underutilized. Mobile health strategies could address this gap but existing evidence is mixed. Therefore, we piloted a pre-post study to assess the impact of patient-directed text messages as a means of improving medication adherence and modifying major health risk behaviors among coronary heart disease (CHD) patients in Hainan, China.

Methods: 92 CVD patients were surveyed between June and August 2015 (before the intervention) and then between October and December 2015 (after 12 week intervention) about (a) medication use (b) smoking status,(c) fruit and vegetable consumption, and (d) physical activity uptake. Acceptability of text-messaging intervention was assessed at follow-up. Descriptive statistics, along with paired comparisons between the pre and post outcomes were conducted using both parametric (t-test) and non-parametric (Wilcoxon signed rank test) methods.

Results: The number of respondents at follow-up was 82 (89% retention rate). Significant improvements were observed for medication adherence (P<0.001) and for the number of cigarettes smoked per day (P=.022). However there was no change in the number of smokers who quitted smoking at follow-up. There were insignificant changes for physical activity (P=0.91) and fruit and vegetable consumption.