Prevention of child behavior problems through universal implementation of a group behavioral family intervention.

The aim of this mental health promotion initiative was to evaluate the effectiveness of a universally delivered group behavioral family intervention (BFI) in preventing behavior problems in children. This study investigates the transferability of an efficacious clinical program to a universal prevention intervention delivered through child and community health services targeting parents of preschoolers within a metropolitan health region. A quasiexperimental two-group (BFI, n=804 vs. Comparison group, n=806) longitudinal design followed preschool aged children and their parents over a 2-year period. BFI was associated with significant reductions in parent-reported levels of dysfunctional parenting and parent-reported levels of child behavior problems. Effect sizes on child behavior problems ranged from large (.83) to moderate (.47). Positive and significant effects were also observed in parent mental health, marital adjustment, and levels of child rearing conflict. Findings are discussed with respect to their implication for significant population reductions in child behavior problems as well as the pragmatic challenges for prevention science in encouraging both the evaluation and uptake of preventive initiatives in real world settings.

An adaptive neural-wavelet model for short term load forecasting

This paper proposed a novel model for short term load forecast in the competitive electricity market. The prior electricity demand data are treated as time series. The forecast model is based on wavelet multi-resolution decomposition by autocorrelation shell representation and neural networks (multilayer perceptrons, or MLPs) modeling of wavelet coefficients. To minimize the influence of noisy low level coefficients, we applied the practical Bayesian method Automatic Relevance Determination (ARD) model to choose the size of MLPs, which are then trained to provide forecasts. The individual wavelet domain forecasts are recombined to form the accurate overall forecast. The proposed method is tested using Queensland electricity demand data from the Australian National Electricity Market. (C) 2001 Elsevier Science B.V. All rights reserved.