98 research outputs found
Mega‐analysis methods in ENIGMA: the experience of the generalized anxiety disorder working group
Pathways through Adolescenc
Psychosocial Treatment of Children in Foster Care: A Review
A substantial number of children in foster care exhibit psychiatric difficulties. Recent epidemiologi-cal and historical trends in foster care, clinical findings about the adjustment of children in foster care, and adult outcomes are reviewed, followed by a description of current approaches to treatment and extant empirical support. Available interventions for these children can be categorized as either symptom-focused or systemic, with empirical support for specific methods ranging from scant to substantial. Even with treatment, behavioral and emotional problems often persist into adulthood, resulting in poor functional outcomes. We suggest that self-regulation may be an important mediat-ing factor in the appearance of emotional and behavioral disturbance in these children
Structural brain correlates of childhood inhibited temperament: an ENIGMA-Anxiety Mega-analysis
NWORubicon 019.201SG.022Pathways through Adolescenc
Brain-based classification of youth with anxiety disorders: transdiagnostic examinations within the ENIGMA-Anxiety database using machine learning
Neuroanatomical findings on youth anxiety disorders are notoriously difficult to replicate, small in effect size and have limited clinical relevance. These concerns have prompted a paradigm shift toward highly powered (that is, big data) individual-level inferences, which are data driven, transdiagnostic and neurobiologically informed. Here we built and validated supervised neuroanatomical machine learning models for individual-level inferences, using a case–control design and the largest known neuroimaging database on youth anxiety disorders: the ENIGMA-Anxiety Consortium (N = 3,343; age = 10–25 years; global sites = 32). Modest, yet robust, brain-based classifications were achieved for specific anxiety disorders (panic disorder), but also transdiagnostically for all anxiety disorders when patients were subgrouped according to their sex, medication status and symptom severity (area under the receiver operating characteristic curve, 0.59–0.63). Classifications were driven by neuroanatomical features (cortical thickness, cortical surface area and subcortical volumes) in fronto-striato-limbic and temporoparietal regions. This benchmark study within a large, heterogeneous and multisite sample of youth with anxiety disorders reveals that only modest classification performances can be realistically achieved with machine learning using neuroanatomical data.NWORubicon 019.201SG.022Advanced Behavioural Research MethodsHealth and Well-bein
The development of inversion in wh-questions: A reply to Van Valin
Item does not contain fulltextVan Valin (Journal of Child Language 29, 2002, 161-75) presents a critique of Rowland & Pine (Journal of Child Language 27, 2000, 157-81) and argues that the wh-question data from Adam (in Brown, A first language, Cambridge, MA, 1973) cannot be explained in terms of input frequencies as we suggest. Instead, he suggests that the data can be more successfully accounted for in terms of Role and Reference Grammar. In this note we re-examine the pattern of inversion and uninversion in Adam's wh-questions and argue that the RRG explanation cannot account for some of the developmental facts it was designed to explain.16 p
- …