299 research outputs found

    Subtypes of Aggressive Behavior in Children with Autism in the Context of Emotion Recognition, Hostile Attribution Bias, and Dysfunctional Emotion Regulation

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    The causes of aggressive behavior in children with autism are poorly understood, which limits treatment options. Therefore, this study used behavioral testing and parent reports of 60 children with autism to investigate the interplay of emotion misinterpretation and hostile attribution bias in the prediction of different aggressive behaviors. Further, the additional impact of dysfunctional emotion regulation was examined. Path analyses indicated that hostile attribution bias increased verbal and covert aggression but not physical aggression and bullying. Dysfunctional emotion regulation had an additional impact on bullying, verbal aggression, and covert aggression. Emotion recognition was positively associated with hostile attribution bias. These findings provide a first insight into a complex interplay of socio-emotional variables; longitudinal studies are needed to examine causal relationships.stiftung irene (germany)berlin school of mind and brainmedical-scientific funds of the mayor of vienna (austria)Humboldt-UniversitÀt zu Berlin (1034)Peer Reviewe

    The contribution of parent and youth information to identify mental health disorders or problems in adolescents

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    BACKGROUND Discrepancies between multiple informants often create considerable uncertainties in delivering services to youth. The present study assessed the ability of the parent and youth scales of the Strength and Difficulties Questionnaire (SDQ) to predict mental health problems/disorders across several mental health domains as validated against two contrasting indices of validity for psychopathology derived from the Development and Well Being Assessment (DAWBA): (1) an empirically derived computer algorithm and (2) expert based ICD-10 diagnoses. METHODS Ordinal and logistic regressions were used to predict any problems/disorders, emotional problems/disorders and behavioural problems/disorders in a community sample (n = 252) and in a clinic sample (n = 95). RESULTS The findings were strikingly similar in both samples. Parent and youth SDQ scales were related to any problem/disorder. Youth SDQ symptom and impact had the strongest association with emotional problems/disorder and parent SDQ symptom score were most strongly related to behavioural problems/disorders. Both the SDQ total and the impact scores significantly predicted emotional problems/disorders in males whereas this was the case only for the total SDQ score in females. CONCLUSION The present study confirms and expands previous findings on parent and youth informant validity. Clinicians should include both parent and youth for identifying any mental health problems/disorders, youth information for detecting emotional problems/disorders, and parent information to detect behavioural problems/disorders. Not only symptom scores but also impact measures may be useful to detect emotional problems/disorders, particularly in male youth

    Identifying predictive features of autism spectrum disorders in a clinical sample of adolescents and adults using machine learning

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    Diagnosing autism spectrum disorders (ASD) is a complicated, time-consuming process which is particularly challenging in older individuals. One of the most widely used behavioral diagnostic tools is the Autism Diagnostic Observation Schedule (ADOS). Previous work using machine learning techniques suggested that ASD detection in children can be achieved with substantially fewer items than the original ADOS. Here, we expand on this work with a specific focus on adolescents and adults as assessed with the ADOS Module 4. We used a machine learning algorithm (support vector machine) to examine whether ASD detection can be improved by identifying a subset of behavioral features from the ADOS Module 4 in a routine clinical sample of N = 673 high-functioning adolescents and adults with ASD (n = 385) and individuals with suspected ASD but other best-estimate or no psychiatric diagnoses (n = 288). We identified reduced subsets of 5 behavioral features for the whole sample as well as age subgroups (adolescents vs. adults) that showed good specificity and sensitivity and reached performance close to that of the existing ADOS algorithm and the full ADOS, with no significant differences in overall performance. These results may help to improve the complicated diagnostic process of ASD by encouraging future efforts to develop novel diagnostic instruments for ASD detection based on the identified constructs as well as aiding clinicians in the difficult question of differential diagnosis

    Exploiting moderate hypoxia to benefit patients with brain disease: Molecular mechanisms and translational research in progress

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    Hypoxia is increasingly recognized as an important physiological driving force. A specific transcriptional program, induced by a decrease in oxygen (O2_{2}) availability, for example, inspiratory hypoxia at high altitude, allows cells to adapt to lower O2_{2} and limited energy metabolism. This transcriptional program is partly controlled by and partly independent of hypoxia‐inducible factors. Remarkably, this same transcriptional program is stimulated in the brain by extensive motor‐cognitive exercise, leading to a relative decrease in O2_{2} supply, compared to the acutely augmented O2_{2} requirement. We have coined the term “functional hypoxia” for this important demand‐responsive, relative reduction in O2_{2} availability. Functional hypoxia seems to be critical for enduring adaptation to higher physiological challenge that includes substantial “brain hardware upgrade,” underlying advanced performance. Hypoxia‐induced erythropoietin expression in the brain likely plays a decisive role in these processes, which can be imitated by recombinant human erythropoietin treatment. This article review presents hints of how inspiratory O2_{2} manipulations can potentially contribute to enhanced brain function. It thereby provides the ground for exploiting moderate inspiratory plus functional hypoxia to treat individuals with brain disease. Finally, it sketches a planned multistep pilot study in healthy volunteers and first patients, about to start, aiming at improved performance upon motor‐cognitive training under inspiratory hypoxia

    How Do Adults with Autism Spectrum Disorder Participate in the Labor Market? A German Multi-center Survey

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    International studies show disadvantages for adults with autism spectrum disorder (ASD) in the labor market. Data about their participation in the German labor market are scarce. The aim of this study was to examine the integration of adults with ASD in the German labor market in terms of education, employment and type of occupation by means of a cross-sectional-study, using a postal questionnaire. Findings show above average levels of education for adults with ASD compared to the general population of Germany and simultaneously, below average rates of employment and high rates of financial dependency. That indicates a poor integration of adults with ASD in the German labor market and emphasizes the need for vocational support policies for adults with ASD

    Open video data sharing in developmental and behavioural science

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    Video recording is a widely used method for documenting infant and child behaviours in research and clinical practice. Video data has rarely been shared due to ethical concerns of confidentiality, although the need of shared large-scaled datasets remains increasing. This demand is even more imperative when data-driven computer-based approaches are involved, such as screening tools to complement clinical assessments. To share data while abiding by privacy protection rules, a critical question arises whether efforts at data de-identification reduce data utility? We addressed this question by showcasing the Prechtl's general movements assessment (GMA), an established and globally practised video-based diagnostic tool in early infancy for detecting neurological deficits, such as cerebral palsy. To date, no shared expert-annotated large data repositories for infant movement analyses exist. Such datasets would massively benefit training and recalibration of human assessors and the development of computer-based approaches. In the current study, sequences from a prospective longitudinal infant cohort with a total of 19451 available general movements video snippets were randomly selected for human clinical reasoning and computer-based analysis. We demonstrated for the first time that pseudonymisation by face-blurring video recordings is a viable approach. The video redaction did not affect classification accuracy for either human assessors or computer vision methods, suggesting an adequate and easy-to-apply solution for sharing movement video data. We call for further explorations into efficient and privacy rule-conforming approaches for deidentifying video data in scientific and clinical fields beyond movement assessments. These approaches shall enable sharing and merging stand-alone video datasets into large data pools to advance science and public health

    The empirical replicability of task-based fMRI as a function of sample size

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    Replicating results (i.e. obtaining consistent results using a new independent dataset) is an essential part of good science. As replicability has consequences for theories derived from empirical studies, it is of utmost importance to better understand the underlying mechanisms influencing it. A popular tool for non-invasive neuroimaging studies is functional magnetic resonance imaging (fMRI). While the effect of underpowered studies is well documented, the empirical assessment of the interplay between sample size and replicability of results for task-based fMRI studies remains limited. In this work, we extend existing work on this assessment in two ways. Firstly, we use a large database of 1400 subjects performing four types of tasks from the IMAGEN project to subsample a series of independent samples of increasing size. Secondly, replicability is evaluated using a multi-dimensional framework consisting of 3 different measures: (un)conditional test-retest reliability, coherence and stability. We demonstrate not only a positive effect of sample size, but also a trade-off between spatial resolution and replicability. When replicability is assessed voxelwise or when observing small areas of activation, a larger sample size than typically used in fMRI is required to replicate results. On the other hand, when focussing on clusters of voxels, we observe a higher replicability. In addition, we observe variability in the size of clusters of activation between experimental paradigms or contrasts of parameter estimates within these
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