The interplay of microscopic and mesoscopic structure in complex networks

Not all nodes in a network are created equal. Differences and similarities exist at both individual node and group levels. Disentangling single node from group properties is crucial for network modeling and structural inference. Based on unbiased generative probabilistic exponential random graph models and employing distributive message passing techniques, we present an efficient algorithm that allows one to separate the contributions of individual nodes and groups of nodes to the network structure. This leads to improved detection accuracy of latent class structure in real world data sets compared to models that focus on group structure alone. Furthermore, the inclusion of hitherto neglected group specific effects in models used to assess the statistical significance of small subgraph (motif) distributions in networks may be sufficient to explain most of the observed statistics. We show the predictive power of such generative models in forecasting putative gene-disease associations in the Online Mendelian Inheritance in Man (OMIM) database. The approach is suitable for both directed and undirected uni-partite as well as for bipartite networks

Exploring Predictors of Outcome in the Psychosis Prodrome: Implications for Early Identification and Intervention

Functional disability is a key component of many psychiatric illnesses, particularly schizophrenia. Impairments in social and role functioning are linked to cognitive deficits, a core feature of psychosis. Retrospective analyses demonstrate that substantial functional decline precedes the onset of psychosis. Recent investigations reveal that individuals at clinical-high-risk (CHR) for psychosis show impairments in social relationships, work/school functioning and daily living skills. CHR youth also demonstrate a pattern of impairment across a range of cognitive domains, including social cognition, which is qualitatively similar to that of individuals with schizophrenia. While many studies have sought to elucidate predictors of clinical deterioration, specifically the development of schizophrenia, in such CHR samples, few have investigated factors relevant to psychosocial outcome. This review integrates recent findings regarding cognitive and social-cognitive predictors of outcome in CHR individuals, and proposes potential directions for future research that will contribute to targeted interventions and improved outcome for at-risk youth

Child and Adolescent Psychiatrists' Reported Monitoring Behaviors for Second-Generation Antipsychotics

Objective: The number of children and adolescents (hereafter referred to as “children”) who have been prescribed second-generation antipsychotics (SGAs) has increased over the last decade, but little is known about monitoring practices in pediatric patients who are vulnerable to adverse effects. We examined factors associated with psychiatrists' self-reported monitoring of children who were prescribed SGAs. Methods: A survey was mailed to a national, randomly selected sample of 1600 child and adolescent psychiatrists from the American Medical Association mailing list. Using logistic regression, we tested whether psychiatrist characteristics, attitudes, and practice characteristics were associated with monitoring (baseline and/or periodic) the following: Patient history, height and weight, blood pressure, waist circumference, lipid and glucose levels, and electrocardiogram. Results: Among the analytic sample of 308, at least two thirds reported monitoring patient history, height and weight, blood pressure, and fasting plasma lipids and glucose; 23% reported monitoring waist circumference; and 12% reported conducting an electrocardiogram. More than one third stated that they routinely monitored thyroid levels and more than half reported monitoring complete blood count and electrolytes/blood urea nitrogen. Psychiatrists reporting that they were able to measure vital signs on site were more likely to measure height and weight. Those who reported feeling comfortable conducting a physical examination were more likely to measure blood pressure. Those answering that the risk of metabolic syndrome was low were less likely to measure blood pressure and waist circumference. Being board certified and able to measure vital signs on site were associated with more monitoring of glucose and lipid levels. Conversely, years in practice and feeling that patients were nonadherent with blood work were associated with less monitoring of glucose and lipid levels. Conclusions: In this sample, inconsistent monitoring patterns of children prescribed SGAs were found. Efforts to communicate guidelines' evidence base and improve office capacity to measure and track adverse effects are needed to increase appropriate adverse effect monitoring in children who have been prescribed SGAs