Attention Performance in an Epidemiological Sample of Urban Children: The Role of Gender and Verbal Intelligence

We administered a comprehensive attentional battery to an epidemiologically defined sample of 435 first and second-grade children to assess the influence of gender and verbal intelligence on attention. The battery included three versions of the continuous performance test (CPT), two digit cancellation tasks, three subtests from the WISC-R, and the Wisconsin Card Sorting Test. The results indicated that both gender and intelligence had an impact on attentional performance. Girls performed better than boys; they made fewer errors on the CPT and obtained higher scores on the digit cancellation task and the Coding subtest of the WISC-R. Children with higher verbal intelligence also performed better on the attentional tests, but this advantage was not observed across measures or levels of performance. For example, children with limited verbal skills performed significantly worse than their peers only in measures with high processing demands(the degraded CPT and the distraction version of the digit cancellation task)

A computational future for preventing HIV in minority communities: How advanced technology can improve implementation of effective programs

Abstract African Americans and Hispanics in the U.S. have much higher rates of HIV than non-minorities. There is now strong evidence that a range of behavioral interventions are efficacious in reducing sexual risk behavior in these populations. While a handful of these programs are just beginning to be disseminated widely, we still have not implemented effective programs to a level that would reduce the population incidence of HIV for minorities. We propose that innovative approaches involving computational technologies be explored for their use in both developing new interventions as well as in supporting wide-scale implementation of effective behavioral interventions. Mobile technologies have a place in both of these activities. First, mobile technologies can be used in sensing contexts and interacting to the unique preferences and needs of individuals at times where intervention to reduce risk would be most impactful. Secondly, mobile technologies can be used to improve the delivery of interventions by facilitators and their agencies. Systems science methods, including social network analysis, agent based models, computational linguistics, intelligent data analysis, and systems and software engineering all have strategic roles that can bring about advances in HIV prevention in minority communities. Using an existing mobile technology for depression and three effective HIV prevention programs, we illustrate how eight areas in the intervention/implementation process can use innovative computational approaches to advance intervention adoption, fidelity, and sustainability

The effect of the level of aggression in the first grade classroom on the course and malleability of aggressive behavior into middle school

This paper is on the influences of the classroom context on the course and malleability of aggressive behavior from entrance into first grade through the transition into middle school. Nineteen public elementary schools participated in developmental epidemiologically based preventive trials in first and second grades, one of which was directed at reducing aggressive, disruptive behavior. At the start of first grade, schools and teachers were randomly assigned to intervention or control conditions. Children within each school were assigned sequentially to classrooms from alphabetized lists, followed by checking to insure balanced assignment based on kindergarten behavior. Despite these procedures, by the end of first quarter, classrooms within schools differed markedly in levels of aggressive behavior. Children were followed through sixth grade, where their aggressive behavior was rated by middle school teachers. Strong interactive effects were found on the risk of being highly aggressive in middle school between the level of aggressive behavior in the first grade classrooms and each boy's own level of aggressive, disruptive behavior in first grade. The more aggressive first grade boys who were in higher aggressive first grade classrooms were at markedly increased risk, compared both to the median first grade boys, and compared to aggressive males in lower aggressive first grade classrooms. Boys were already behaving more aggressively than girls in first grade; and no similar classroom aggression effect was found among girls, although girls' own aggressive behavior did place them at increased risk. The preventive intervention effect, already reported elsewhere to reduce aggressive behavior among the more aggressive males, appeared to do so by reducing high levels of classroom aggression. First grade males' own poverty level was associated with higher risk of being more aggressive, disruptive in first grade, and thereby increased their vulnerability to classroom level of aggression. Both boys and girls in schools in poor communities were at increased risk of being highly aggressive in middle school regardless of their levels of aggressive behavior in first grade. These results are discussed in terms of life course/social field theory as applied to the role of contextual influences on the development and etiology of severe aggressive behavior

Testing moderation in network meta-analysis with individual participant data.

Meta-analytic methods for combining data from multiple intervention trials are commonly used to estimate the effectiveness of an intervention. They can also be extended to study comparative effectiveness, testing which of several alternative interventions is expected to have the strongest effect. This often requires network meta-analysis (NMA), which combines trials involving direct comparison of two interventions within the same trial and indirect comparisons across trials. In this paper, we extend existing network methods for main effects to examining moderator effects, allowing for tests of whether intervention effects vary for different populations or when employed in different contexts. In addition, we study how the use of individual participant data (IPD) may increase the sensitivity of NMA for detecting moderator effects, as compared to aggregate data NMA that employs study-level effect sizes in a meta-regression framework. A new network meta-analysis diagram is proposed. We also develop a generalized multilevel model for NMA that takes into account within- and between-trial heterogeneity, and can include participant-level covariates. Within this framework we present definitions of homogeneity and consistency across trials. A simulation study based on this model is used to assess effects on power to detect both main and moderator effects. Results show that power to detect moderation is substantially greater when applied to IPD as compared to study-level effects. We illustrate the use of this method by applying it to data from a classroom-based randomized study that involved two sub-trials, each comparing interventions that were contrasted with separate control groups