Feasibility of guided CBT self-help for childhood anxiety disorders in primary care

Anxiety disorders in childhood are common, disabling and run a chronic course. Cognitive Behaviour Therapy (CBT) effective but is expensive and trained therapists are scarce. Guided self-help treatments may be a means of widening access to treatment. This study aimed to examine the feasibility of guided CBT self-help for childhood anxiety disorders in Primary Care, specifically in terms of therapist adherence, patient and therapist satisfaction and clinical gain. Participants were children aged 5-12 years referred to two Primary Child and Adolescent Mental Health Services (PCAMHSs) in Oxfordshire, UK, who met diagnostic criteria for a primary anxiety disorder. Of the 52 eligible children, 41 anxious children were assessed for anxiety severity and interference before and after receiving CBT self-help, delivered via the parent (total therapy time= 5 hours) by Primary Mental Health Workers (PMHWs). Therapy sessions were rated for treatment adherence and patients and PMHWs completed satisfaction questionnaires after treatment completion. Over 80% of therapy sessions were rated at a high level of treatment adherence. Parents and PMHWs reported high satisfaction with the treatment. 61% of the children assessed no longer met criteria for their primary anxiety disorder diagnosis following treatment, and 76% were rated as ‘much’/’very much’ improved on the Clinician’s Global Impression-Improvement scale. There were significant reductions on parent and child report measures of anxiety symptoms, interference, and depression. Preliminary exploration indicated that parental anxiety was associated with child treatment outcome. The findings suggest that guided CBT self-help represents a promising treatment for childhood anxiety in primary care.

A neural network enhanced generalized minimum variance self-tuning proportional, integral and derivative control algorithm for complex dynamic systems

A neural network enhanced proportional, integral and derivative (PID) controller is presented that combines the attributes of neural network learning with a generalized minimum-variance self-tuning control (STC) strategy. The neuro PID controller is structured with plant model identification and PID parameter tuning. The plants to be controlled are approximated by an equivalent model composed of a simple linear submodel to approximate plant dynamics around operating points, plus an error agent to accommodate the errors induced by linear submodel inaccuracy due to non-linearities and other complexities. A generalized recursive least-squares algorithm is used to identify the linear submodel, and a layered neural network is used to detect the error agent in which the weights are updated on the basis of the error between the plant output and the output from the linear submodel. The procedure for controller design is based on the equivalent model, and therefore the error agent is naturally functioned within the control law. In this way the controller can deal not only with a wide range of linear dynamic plants but also with those complex plants characterized by severe non-linearity, uncertainties and non-minimum phase behaviours. Two simulation studies are provided to demonstrate the effectiveness of the controller design procedure.

Generalized neurofuzzy network modeling algorithms using Bezier-Bernstein polynomial functions and additive decomposition

This paper introduces a new neurofuzzy model construction algorithm for nonlinear dynamic systems based upon basis functions that are Bezier-Bernstein polynomial functions. This paper is generalized in that it copes with n-dimensional inputs by utilising an additive decomposition construction to overcome the curse of dimensionality associated with high n. This new construction algorithm also introduces univariate Bezier-Bernstein polynomial functions for the completeness of the generalized procedure. Like the B-spline expansion based neurofuzzy systems, Bezier-Bernstein polynomial function based neurofuzzy networks hold desirable properties such as nonnegativity of the basis functions, unity of support, and interpretability of basis function as fuzzy membership functions, moreover with the additional advantages of structural parsimony and Delaunay input space partition, essentially overcoming the curse of dimensionality associated with conventional fuzzy and RBF networks. This new modeling network is based on additive decomposition approach together with two separate basis function formation approaches for both univariate and bivariate Bezier-Bernstein polynomial functions used in model construction. The overall network weights are then learnt using conventional least squares methods. Numerical examples are included to demonstrate the effectiveness of this new data based modeling approach.

Interpretation bias and anxiety in childhood: stability, specificity and longitudinal associations

Background: Biases in the interpretation of ambiguous material are central to cognitive models of anxiety; however, understanding of the association between interpretation and anxiety in childhood is limited. To address this, a prospective investigation of the stability and specificity of anxious cognitions and anxiety and the relationship between these factors was conducted. Method: Sixty-five children (10–11 years) from a community sample completed measures of self-reported anxiety, depression, and conduct problems, and responded to ambiguous stories at three time points over one-year. Results: Individual differences in biases in interpretation of ambiguity (specifically “anticipated distress” and “threat interpretation”) were stable over time. Furthermore, anticipated distress and threat interpretation were specifically associated with anxiety symptoms. Distress anticipation predicted change in anxiety symptoms over time. In contrast, anxiety scores predicted change in threat interpretation over time. Conclusions: The results suggest that different cognitive constructs may show different longitudinal links with anxiety. These preliminary findings extend research and theory on anxious cognitions and their link with anxiety in children, and suggest that these cognitive processes may be valuable targets for assessment and intervention.

Lorrie Moore collection, 'A Little Ethnic Kink Is Always Good to See”: Jewish performance anxiety and anti-passing in the fiction of Lorrie Moore

This essay explores the ways in which the performance of Jewish identity (in the sense both of representing Jewish characters and of writing about those characters’ conscious and unconscious renditions of their Jewishness) is a particular concern (in both senses of the word) for Lorrie Moore. Tracing Moore's representations of Jewishness over the course of her career, from the early story “The Jewish Hunter” through to her most recent novel, A Gate at the Stairs, I argue that it is characterized by (borrowing a phrase from Moore herself) “performance anxiety,” an anxiety that manifests itself in awkward comedy and that can be read both in biographical terms and as an oblique commentary on, or reworking of, the passing narrative, which I call “anti-passing.” Just as passing narratives complicate conventional ethno-racial definitions so Moore's anti-passing narratives, by representing Jews who represent themselves as other to themselves, as well as to WASP America, destabilize the category of Jewishness and, by implication, deconstruct the very notion of ethnic categorization.

Emotion processing in infancy: specificity in risk for social anxiety and associations with two year outcomes

The current study examined the specificity of patterns of responding to high and low intensity negative emotional expressions of infants of mothers with social phobia, and their association with child outcomes at two years of age. Infants of mothers with social phobia, generalised anxiety disorder (GAD) or no history of anxiety were shown pairs of angry and fearful emotional expressions at 10 weeks of age. Symptoms of social withdrawal, anxiety and sleep problems were assessed at two years of age. Only infants of mothers with social phobia showed a tendency to look away from high intensity fear faces; however infants of mothers with both social phobia and GAD showed a bias towards high intensity angry faces. Among the offspring of mothers with social phobia, anxiety symptoms at two years of age were associated with a preference for high intensity fear faces in infancy. The reverse pattern was found amongst the offspring of non-anxious mothers. These findings suggest a possible specific response to emotional expressions among the children of mothers with social phobia.

Generalized beta generated distributions

This article introduces generalized beta-generated (GBG) distributions. Sub-models include all classical beta-generated, Kumaraswamy-generated and exponentiated distributions. They are maximum entropy distributions under three intuitive conditions, which show that the classical beta generator skewness parameters only control tail entropy and an additional shape parameter is needed to add entropy to the centre of the parent distribution. This parameter controls skewness without necessarily differentiating tail weights. The GBG class also has tractable properties: we present various expansions for moments, generating function and quantiles. The model parameters are estimated by maximum likelihood and the usefulness of the new class is illustrated by means of some real data sets.

Anxiety problems in young people with Asperger syndrome: a case series

It is now well established that the prevalence of mental health difficulties in individuals with autism spectrum disorders (ASD) is considerably higher than in the general population. With recent estimates of the prevalence of autism spectrum disorders being as high as one percent, increasing numbers of children and young people are presenting to local and specialist services with mental health problems in addition to a diagnosis of ASD. Many families report that the impact of the mental health problems can be as or more impairing than the autism spectrum difficulties themselves. Clinical services are frequently called upon to treat these difficulties; however, there is limited evidence for the effectiveness of treatments in this population. This paper reports a case series of children and adolescents with ASD and an anxiety disorder who were treated with a standard cognitive behaviour therapy (CBT) rationale adapted to take account of the neuropsychological features of ASD. Common features of the presentation of the disorders and also treatment processes are discussed.