Cognitive behavioural psychotherapy intervention in childhood sexual abuse: identifying new directions from the literature

The short‐ and long‐term consequences of childhood sexual abuse have been extensively reported. However, for many years there has been an absence of psychological conceptual frameworks for understanding and treating abuse trauma symptoms. This paper reviews a number of outcome studies for the treatment of child sexual abuse where a post‐traumatic stress disorder (PTSD) conceptualization was used to plan treatment interventions. The paper concludes that, contrary to some concerns expressed by clinicians, sexually abused children and their non‐abusing carers can signi?cantly bene?t from cognitive behavioural interventions which use reliving and confrontation of the abusive experience. Notwithstanding this, there is a need for further controlled outcome research of cognitive behavioural interventions using reliving techniques to explore how and why these interventions help in reducing abuse‐related PTSD symptoms. Copyright © 2004 John Wiley & Sons, Ltd.     

Family Dilemmas and Secrets: parents' disclosure of information to their adult offspring with learning disabilities

This paper describes the role parents play in providing knowledge of learning disability to their adult offspring with learning disabilities. Data were derived from an in-depth qualitative study of the nature of parent-adult-offspring co-residence. The findings reveal that while parents recognised and had to deal with the stigma learning disability exerted in their own lives, they had taken steps to prevent their adult offspring from having to deal with similar difficulties. It is argued that it remains the case that learning disability is treated as a stigmatised identity and as such is rendered invisible through the strategic control of information. However, findings point towards the conclusion that there has been a cultural reversal in how this process is managed.     

Predicting the Risk of Biological Invasions Using Environmental Similarity and Transport Network Connectedness

Understanding the risk of biological invasions associated with particular transport pathways and source regions is critical for implementing effective biosecurity management. This may require both a model for physical connectedness between regions, and a measure of environmental similarity, so as to quantify the potential for a species to be transported from a given region and to survive at a destination region. We present an analysis of integrated biosecurity risk into Australia, based on flights and shipping data from each global geopolitical region, and an adaptation of the “range bagging” method to determine environmental matching between regions. Here, we describe global patterns of environmental matching and highlight those regions with many physical connections. We classify patterns of global invasion risk (high to low) into Australian states and territories. We validate our analysis by comparison with global presence data for 844 phytophagous insect pest species, and produce a list of high‐risk species not previously known to be present in Australia. We determined that, of the insect pest species used for validation, the species most likely to be present in Australia were those also present in geopolitical regions with high transport connectivity to Australia, and those regions that were geographically close, and had similar environments.     

Real nonparametric regression using complex wavelets

Summary.  Wavelet shrinkage is an effective nonparametric regression technique, especially when the underlying curve has irregular features such as spikes or discontinuities. The basic idea is simple: take the discrete wavelet transform of data consisting of a signal corrupted by noise; shrink or remove the wavelet coefficients to remove the noise; then invert the discrete wavelet transform to form an estimate of the true underlying curve. Various researchers have proposed increasingly sophisticated methods of doing this by using real-valued wavelets. Complex-valued wavelets exist but are rarely used. We propose two new complex-valued wavelet shrinkage techniques: one based on multiwavelet style shrinkage and the other using Bayesian methods. Extensive simulations show that our methods almost always give significantly more accurate estimates than methods based on real-valued wavelets. Further, our multiwavelet style shrinkage method is both simpler and dramatically faster than its competitors. To understand the excellent performance of this method we present a new risk bound on its hard thresholded coefficients.     

Strong convergence rates of probabilistic integrators for ordinary differential equations

Probabilistic integration of a continuous dynamical system is a way of systematically introducing discretisation error, at scales no larger than errors introduced by standard numerical discretisation, in order to enable thorough exploration of possible responses of the system to inputs. It is thus a potentially useful approach in a number of applications such as forward uncertainty quantification, inverse problems, and data assimilation. We extend the convergence analysis of probabilistic integrators for deterministic ordinary differential equations, as proposed by Conrad et al. (Stat Comput 27(4):1065–1082, 2017. https://doi.org/10.1007/s11222-016-9671-0), to establish mean-square convergence in the uniform norm on discrete- or continuous-time solutions under relaxed regularity assumptions on the driving vector fields and their induced flows. Specifically, we show that randomised high-order integrators for globally Lipschitz flows and randomised Euler integrators for dissipative vector fields with polynomially bounded local Lipschitz constants all have the same mean-square convergence rate as their deterministic counterparts, provided that the variance of the integration noise is not of higher order than the corresponding deterministic integrator. These and similar results are proven for probabilistic integrators where the random perturbations may be state-dependent, non-Gaussian, or non-centred random variables.

     

The Statistical Analysis of Preference Data

A new statistic and a new method of analysis are proposed for data where a sample of respondents provides a preference ordering of some treatments. The new preference statistic is compared with the Friedman statistic, particularly for an example where 12 home owners each ranked four grasses. The new analysis provides a more natural and less misleading assessment of where the differences occur than an analysis based on the rank sums of the Friedman statistic. The new analysis is also more robust to deviations from the classical location problem, is not related to election methods known to have undesirable characteristics and adheres to the Condorcet criterion for election methods.     

Families in the Life Course: Interdependency of Roles,Role Configurations,and Pathways

Families are central in the unfolding life course. They have both internal and external dynamics that reflect and characterize the modern life span, and a life course perspective has particular utility for understanding the role and implications of families for individuals and society. The purpose of this paper is 3‐fold. First, we offer a family life course perspective that delineates core concepts of roles, role configurations, and pathways, specifies the links between them, and highlights the importance of linked lives and structural context. Second, we elaborate a latent class approach for modeling the multilayered dynamic interdependencies that characterize modern family life. Third, we provide an empirical example by considering the timing of childbearing, teen parenthood, and its place in the transition to adulthood using women's data from the National Longitudinal Survey of Youth 1979 (N= 2,191). We conclude by discussing further avenues of family research that are enhanced with a life course approach and complementary latent structure methodology.