The Impact of Neighborhood Factors on the Well-Being of Survivors of Intimate Partner Violence Over Time

Intimate partner violence (IPV) is a pervasive social problem impacting the psychological well-being of millions of US women annually. The extant literature draws our attention to the devastating mental health effects of IPV, but largely overlooks how ecological factors may further explain survivors' well-being. This study examined how neighborhood disadvantage may contribute to survivors' compromised well-being, in addition to the abuse women experienced. Neighborhood disorder and fear of victimization significantly impacted survivors' well-being, over and above abuse. Although between-women effects of neighborhood disorder and fear were unrelated to change in women's depression or quality of life (QOL), significant within-woman effects were detected. Change in neighborhood disorder was negatively associated with change in QOL, and this relationship was fully mediated by fear. While no direct relationship between change in neighborhood disorder and depression was detected, an indirect effect through survivors' fear was revealed. Implications for future research and practice are discussed.     

Modulation of N400 in chronic non-fluent aphasia using low frequency Repetitive Transcranial Magnetic Stimulation (rTMS)

Low frequency Repetitive Transcranial Magnetic Stimulation (rTMS) has previously been applied to language homologues in non-fluent populations of persons with aphasia yielding significant improvements in behavioral language function up to 43 months post stimulation. The present study aimed to investigate the electrophysiological correlates associated with the application of rTMS through measurement of the semantic based N400 Event-related brain potentials (ERP) component. Low frequency (1 Hz) rTMS was applied to the anterior portion of the homologue to Broca’s area (pars triangularis), for 20 min per day for 10 days, using a stereotactic neuronavigational system. Twelve non-fluent persons with aphasia, 2-6 years post stroke were stimulated. Six participants were randomly assigned to receive real stimulation and six participants were randomly assigned to receive a blind sham control condition. ERP measures were recorded at baseline, 1 week and 2 months subsequent to stimulation. The findings demonstrate treatment related changes observed in the stimulation group when compared to the placebo control group at 2 months post stimulation indicating neuromodulation of N400 as a result of rTMS. No treatment related changes were identified in the stimulation group, when compared to the sham group from baseline to 1 week post stimulation. The electrophysiological results represent the capacity of rTMS to modulate neural language networks and measures of lexical-semantic function in participants with non-fluent aphasia and suggest that time may be an important factor in brain reorganization subsequent to rTMS.     

But is it evolution…?

We applaud Müller & Schumann (M&S) for bringing needed attention to the problem of motivation for common non-addictive drug use, as opposed to the usual focus on exotic drugs and addiction. Unfortunately, their target article has many underdeveloped and sometimes contradictory ideas. Here, we will focus on three key issues.     

By the numbers: Structure-seeking individuals prefer quantitative over qualitative representations of personal value to compensate for the threat of unclear performance contingencies

What combination of dispositional and situational factors leads people to represent their personal value in quantitative terms (e.g., salary) rather than qualitative terms (e.g., virtue)? Integrating research on quantitative information seeking, dispositional epistemic motivation, and learned helplessness, the current article hypothesized that individuals high, but not low, in uncertainty avoidance (measured with the Personal Need for Structure Scale [PNS]) would prefer quantitative (over qualitative) value representations to compensate for the diminished self-esteem certainty caused by exposure to unclear performance contingencies. Accordingly, in Study 1 high-PNS participants exposed to unclear (vs. clear) performance contingencies in one domain (visual intelligence) preferred a quantitative value representation in another domain (verbal intelligence). Study 2 showed that this effect is mediated by self-esteem certainty, not self-esteem level. Study 3 included a failure feedback condition to further isolate the role of epistemic motivation, as distinct from self-enhancement motivation, in driving the tendency to quantify personal value.     

The Role of Parental Distress in Moderating the Influence of Child Neglect on Maladjustment

Despite pervasive evidence of the harmful impact of neglect on children’s adjustment, individual differences in adaptation persist. This study examines parental distress as a contextual factor that may moderate the relation between neglect and child adjustment, while considering the specificity of the relation between neglect and internalizing versus externalizing problems. In a sample of 66 children (33 with a documented child protective services history of neglect prior to age six), neglect predicted internalizing, and to a lesser extent externalizing, problems as rated by teachers at age seven. Parental distress moderated the relation between neglect and internalizing, but not externalizing, problems. Specifically, higher levels of neglect predicted more internalizing problems only among children of distressed parents. These findings indicate that parent-level variables are important to consider in evaluating the consequences of neglect, and point to the importance of considering contextual factors when identifying those children most at risk following neglect.     

Using generalized additive (mixed) models to analyze single case designs

This article shows how to apply generalized additive models and generalized additive mixed models to single-case design data. These models excel at detecting the functional form between two variables (often called trend), that is, whether trend exists, and if it does, what its shape is (e.g., linear and nonlinear). In many respects, however, these models are also an ideal vehicle for analyzing single-case designs because they can consider level, trend, variability, overlap, immediacy of effect, and phase consistency that single-case design researchers examine when interpreting a functional relation. We show how these models can be implemented in a wide variety of ways to test whether treatment is effective, whether cases differ from each other, whether treatment effects vary over cases, and whether trend varies over cases. We illustrate diagnostic statistics and graphs, and we discuss overdispersion of data in detail, with examples of quasibinomial models for overdispersed data, including how to compute dispersion and quasi-AIC fit indices in generalized additive models. We show how generalized additive mixed models can be used to estimate autoregressive models and random effects and discuss the limitations of the mixed models compared to generalized additive models. We provide extensive annotated syntax for doing all these analyses in the free computer program R.