Study protocol of the ASD-Net, the German research consortium for the study of Autism Spectrum Disorder across the lifespan: from a better etiological understanding, through valid diagnosis, to more effective health care

The Transdiagnostic Connectome Project: a richly phenotyped open dataset for advancing the study of brain-behavior relationships in psychiatry

An important aim in psychiatry is the establishment of valid and reliable associations linking profiles of brain functioning to clinically relevant symptoms and behaviors across patient populations. To advance progress in this area, we introduce an open dataset containing behavioral and neuroimaging data from 241 individuals aged 18 to 70, comprising 148 individuals meeting diagnostic criteria for a broad range of psychiatric illnesses and a healthy comparison group of 93 individuals. These data include high-resolution anatomical scans, multiple resting-state, and task-based functional MRI runs. Additionally, participants completed over 50 psychological and cognitive assessments. Here, we detail available behavioral data as well as raw and processed MRI derivatives. Associations between data processing and quality metrics, such as head motion, are reported. Processed data exhibit classic task activation effects and canonical functional network organization. Overall, we provide a comprehensive and analysis-ready transdiagnostic dataset, which we hope will accelerate the identification of illness-relevant features of brain functioning, enabling future discoveries in basic and clinical neuroscience.

Use of complementary and alternative medicine in children affected by oncologic, neurologic and liver diseases: a narrative review

Complementary and alternative medicine (CAM) consist of a broad group of restorative resources often linked to existing local cultures and established health care systems and are also increasingly used in children with some serious illnesses. In this narrative review, we examine the epidemiology of the use, efficacy, and safety of complementary and alternative medicine in pediatric oncology, neurology, and hepatology. We searched for relevant articles published in Pubmed evaluating CAM use and its efficacy in safety in children affected by oncologic, neurologic and liver diseases. CAM is used to improve the success of conventional therapies, but also to alleviate the pain, discomfort, and suffering resulting from the diseases and their treatment, which are often associated with a significant burden of adverse effects. CAM use must be evaluated in children with neurological, oncological and liver diseases.

Conceptualization of the latent structure of autism: further evidence and discussion of dimensional and hybrid models

Autism spectrum disorder (ASD) might be conceptualized as an essentially dimensional, categorical, or hybrid model. Yet, current empirical studies are inconclusive and the latent structure of ASD has explicitly been examined only in a few studies. The aim of our study was to identify and discuss the latent model structure of behavioral symptoms related to ASD and to address the question of whether categories and/or dimensions best represent ASD symptoms. We included data of 2920 participants (1-72 years of age), evaluated with the Autism Diagnostic Observation Schedule (Modules 1-4). We applied latent class analysis, confirmatory factor analysis, and factor mixture modeling and evaluated the model fit by a combination of criteria. Based on the model selection criteria, the model fits, the interpretability as well as the clinical utility we conclude that the hybrid model serves best for conceptualization and assessment of ASD symptoms. It is both grounded in empirical evidence and in clinical usefulness, is in line with the current classification system (DSM-5) and has the potential of being more specific than the dimensional approach (decreasing false positive diagnoses).

Impaired white matter integrity in infants and young children with autism spectrum disorder: What evidence does diffusion tensor imaging provide?

BACKGROUND

Abnormal functional connections are associated with impaired white matter tract integrity in the brain. Diffusion tensor imaging (DTI) is a promising method for evaluating white matter integrity in infants and young children. This work aims to shed light on the location and nature of the decrease in white matter integrity.

METHODS

Here, the results of 19 studies have been presented that investigated white matter integrity in infants and young children (6 months to 12 years) with autism using diffusion tensor imaging.

RESULTS

In most of the reviewed studies, an increase in Fractional Anisotropy (FA) and a decrease in Radial Diffusivity (RD) were reported in Corpus Callosum (CC), Uncinate Fasciculus (UF), Cingulum (Cg), Inferior Longitudinal Fasciculus (ILF), and Superior Longitudinal Fasciculus (SLF), and in the Inferior Fronto-Occipital Fasciculus (IFOF) tract, a decrease in FA and an increase in RD were reported.

CONCLUSION

In the reviewed articles, except for one study, the diffusion indices were different compared to the control group.

Using machine learning to improve diagnostic assessment of ASD in the light of specific differential and co-occurring diagnoses

BACKGROUND

Diagnostic assessment of ASD requires substantial clinical experience and is particularly difficult in the context of other disorders with behavioral symptoms in the domain of social interaction and communication. Observation measures such as the Autism Diagnostic Observation Schedule (ADOS) do not take into account such co-occurring disorders.

METHOD

We used a well-characterized clinical sample of individuals (n = 1,251) that had received detailed outpatient evaluation for the presence of an ASD diagnosis (n = 481) and covered a range of additional overlapping diagnoses, including anxiety-related disorders (ANX, n = 122), ADHD (n = 439), and conduct disorder (CD, n = 194). We focused on ADOS module 3, covering the age range with particular high prevalence of such differential diagnoses. We used machine learning (ML) and trained random forest models on ADOS single item scores to predict a clinical best-estimate diagnosis of ASD in the context of these differential diagnoses (ASD vs. ANX, ASD vs. ADHD, ASD vs. CD), in the context of co-occurring ADHD, and an unspecific model using all available data. We employed nested cross-validation for an unbiased estimate of classification performance and made available a Webapp to showcase the results and feasibility for translation into clinical practice.

RESULTS

We obtained very good overall sensitivity (0.89-0.94) and specificity (0.87-0.89). In particular for individuals with less severe symptoms, our models showed increases of up to 35% in sensitivity or specificity. Furthermore, we analyzed item importance profiles of the ANX, ADHD, and CD models in comparison with the unspecific model revealing distinct patterns of importance for specific ADOS items with respect to differential diagnoses.

CONCLUSIONS

ML-based diagnostic classification may improve clinical decisions by utilizing the full range of information from detailed diagnostic observation instruments such as the ADOS. Importantly, this strategy might be of particular relevance for older children with less severe symptoms for whom the diagnostic decision is often particularly difficult.

A data driven machine learning approach to differentiate between autism spectrum disorder and attention-deficit/hyperactivity disorder based on the best-practice diagnostic instruments for autism

Autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) are two frequently co-occurring neurodevelopmental conditions that share certain symptomatology, including social difficulties. This presents practitioners with challenging (differential) diagnostic considerations, particularly in clinically more complex cases with co-occurring ASD and ADHD. Therefore, the primary aim of the current study was to apply a data-driven machine learning approach (support vector machine) to determine whether and which items from the best-practice clinical instruments for diagnosing ASD (ADOS, ADI-R) would best differentiate between four groups of individuals referred to specialized ASD clinics (i.e., ASD, ADHD, ASD + ADHD, ND = no diagnosis). We found that a subset of five features from both ADOS (clinical observation) and ADI-R (parental interview) reliably differentiated between ASD groups (ASD & ASD + ADHD) and non-ASD groups (ADHD & ND), and these features corresponded to the social-communication but also restrictive and repetitive behavior domains. In conclusion, the results of the current study support the idea that detecting ASD in individuals with suspected signs of the diagnosis, including those with co-occurring ADHD, is possible with considerably fewer items relative to the original ADOS/2 and ADI-R algorithms (i.e., 92% item reduction) while preserving relatively high diagnostic accuracy. Clinical implications and study limitations are discussed.

Mixed-methods investigation of barriers and needs in mental healthcare of adults with autism and recommendations for future care (BarrierfreeASD): study protocol

INTRODUCTION

Autism refers to an early-onset neurodevelopmental condition with characteristic impairments and difficulties in practical living skills, which persist across the lifespan such that adults with autism often require substantial support and comprehensive care. Yet, mental health and other services are frequently unavailable for adults with autism despite considerable need for mental healthcare and individual, familial and socioeconomic burdens. This study will (1) examine current needs, barriers and burdens related to ineffective healthcare of adults with autism in Germany, (2) develop specific recommendations for a need-oriented mental healthcare model and (3) evaluate its future implementation.

METHODS AND ANALYSIS

A mixed-methods design with three phases will be conducted. In phase 1, current mental healthcare for adults with autism will be assessed at three levels (individual, structural and professional) and from three perspectives (adults with autism, relatives and healthcare providers) using (1) focus groups/interviews (qualitative data) and (2) large-scale online surveys (quantitative data). Furthermore, service utilisation and related costs will be estimated. In phase 2, recommendations for a future healthcare model will be derived based on phase 1, considering the heterogeneous and complex needs within the autism spectrum and specifying indications for recommended services. In phase 3, these will again be evaluated by the three stakeholder groups using mixed-methods and analysed regarding feasibility of implementation and cost-effectiveness. Our study will, thus, contribute to a better translation of recommendations into practice to reduce disability, burden and costs related to ineffective healthcare and improve mental health outcomes for adults with autism and those who support them.

ETHICS AND DISSEMINATION

This study was approved by the Local Psychological Ethics Commission of the Center for Psychosocial Medicine at the University Medical Center Hamburg-Eppendorf (LPEK-0227). Findings will be disseminated via scientific meetings and peer-reviewed journals. Cooperating partners and associations will be informed about the study's course and findings by regular newsletters and meetings.

TRIAL REGISTRATION NUMBER

This study protocol was preregistered at the Open Science Framework (osf.io/5x8pg).

Differentiation of autism spectrum disorder and mood or anxiety disorder

LAY ABSTRACT

Symptoms of mood and anxiety disorders overlap with symptoms of autism spectrum disorder, making the diagnostic process challenging. This study found that a combination of communicational deficits and unusual and/or inappropriate social overtures facilitates differentiation between autism spectrum disorder and mood and anxiety disorders. Furthermore, the results confirm the essential need of a behavioral observation with the Autism Diagnostic Observation Schedule in combination with a full Autism Diagnostic Interview-Revised to support diagnostic decisions.

Subdimensions of social-communication behavior in autism-A replication study

Introduction

In order to identify more refined dimensions of social-communication impairments in autism spectrum disorder (ASD) a previous study applied exploratory and confirmatory factor analyses to diagnostic algorithm scores of the autism diagnostic observation schedule (ADOS), Module 3. A three-factor model consisting of repetitive behaviors, impairments in 'Basic Social-Communication' and in 'Interaction quality' (IQ) was established and confirmed. The current study aimed to replicate this model in an independent sample. To advance our understanding of the latent structure of social communication deficits, previous work was complemented by a probabilistic approach.

Methods

Participants (N = 1363) included verbally fluent children and young adults, diagnosed as ASD or non-ASD based on "gold standard" best-estimate clinical diagnosis. Confirmatory factor analysis examined the factor structure of algorithm items from the ADOS Module 3 and correlations with individual characteristics (cognitive abilities, age) were analyzed. Linear Regressions were used to test the contribution of each latent factor to the prediction of an ASD diagnosis. To tackle large inter-correlations of the latent factors, a Bayesian exploratory factor analysis (BEFA) was applied.

Results

Results confirmed the previously reported observation of three latent dimensions in the ADOS algorithm reflecting 'Restricted, Repetitive Behaviors', 'Basic Social-Communication' behaviors and 'Interaction Quality'. All three dimensions contributed independently and additively to the prediction of an ASD diagnosis.

Conclusion

By replicating previous findings in a large clinical sample our results contribute to further conceptualize the social-communication impairments in ASD as two dimensional.

Phenotypic differences between female and male individuals with suspicion of autism spectrum disorder

BACKGROUND

Although autism spectrum disorder (ASD) is a common developmental disorder, our knowledge about a behavioral and neurobiological female phenotype is still scarce. As the conceptualization and understanding of ASD are mainly based on the investigation of male individuals, females with ASD may not be adequately identified by routine clinical diagnostics. The present machine learning approach aimed to identify diagnostic information from the Autism Diagnostic Observation Schedule (ADOS) that discriminates best between ASD and non-ASD in females and males.

METHODS

Random forests (RF) were used to discover patterns of symptoms in diagnostic data from the ADOS (modules 3 and 4) in 1057 participants with ASD (18.1% female) and 1230 participants with non-ASD (17.9% % female). Predictive performances of reduced feature models were explored and compared between females and males without intellectual disabilities.

RESULTS

Reduced feature models relied on considerably fewer features from the ADOS in females compared to males, while still yielding similar classification performance (e.g., sensitivity, specificity).

LIMITATIONS

As in previous studies, the current sample of females with ASD is smaller than the male sample and thus, females may still be underrepresented, limiting the statistical power to detect small to moderate effects.

CONCLUSION

Our results do not suggest the need for new or altered diagnostic algorithms for females with ASD. Although we identified some phenotypic differences between females and males, the existing diagnostic tools seem to sufficiently capture the core autistic features in both groups.

Abilities and Disabilities-Applying Machine Learning to Disentangle the Role of Intelligence in Diagnosing Autism Spectrum Disorders

Objective

Although autism spectrum disorder (ASD) is a relatively common, well-known but heterogeneous neuropsychiatric disorder, specific knowledge about characteristics of this heterogeneity is scarce. There is consensus that IQ contributes to this heterogeneity as well as complicates diagnostics and treatment planning. In this study, we assessed the accuracy of the Autism Diagnostic Observation Schedule (ADOS/2) in the whole and IQ-defined subsamples, and analyzed if the ADOS/2 accuracy may be increased by the application of machine learning (ML) algorithms that processed additional information including the IQ level.

Methods

The study included 1,084 individuals: 440 individuals with ASD (with a mean IQ level of 3.3 ± 1.5) and 644 individuals without ASD (with a mean IQ level of 3.2 ± 1.2). We applied and analyzed Random Forest (RF) and Decision Tree (DT) to the ADOS/2 data, compared their accuracy to ADOS/2 cutoff algorithms, and examined most relevant items to distinguish between ASD and Non-ASD. In sum, we included 49 individual features, independently of the applied ADOS module.

Results

In DT analyses, we observed that for the decision ASD/Non-ASD, solely one to four items are sufficient to differentiate between groups with high accuracy. In addition, in sub-cohorts of individuals with (a) below (IQ level ≥4)/ID and (b) above average intelligence (IQ level ≤ 2), the ADOS/2 cutoff showed reduced accuracy. This reduced accuracy results in (a) a three times higher risk of false-positive diagnoses or (b) a 1.7 higher risk for false-negative diagnoses; both errors could be significantly decreased by the application of the alternative ML algorithms.

Conclusions

Using ML algorithms showed that a small set of ADOS/2 items could help clinicians to more accurately detect ASD in clinical practice across all IQ levels and to increase diagnostic accuracy especially in individuals with below and above average IQ level.

Health Services Use and Costs in Individuals with Autism Spectrum Disorder in Germany: Results from a Survey in ASD Outpatient Clinics

Autism spectrum disorders (ASD) are associated with high services use, but European data on costs are scarce. Utilisation and annual costs of 385 individuals with ASD (aged 4-67 years; 18.2% females; 37.4% IQ < 85) from German outpatient clinics were assessed. Average annual costs per person were 3287 EUR, with psychiatric inpatient care (19.8%), pharmacotherapy (11.1%), and occupational therapy (11.1%) being the largest cost components. Females incurred higher costs than males (4864 EUR vs. 2936 EUR). In a regression model, female sex (Cost Ratio: 1.65), lower IQ (1.90), and Asperger syndrome (1.54) were associated with higher costs. In conclusion, ASD-related health costs are comparable to those of schizophrenia, thus underlining its public health relevance. Higher costs in females demand further research.

Assessment of Reward-Related Brain Function After a Single Dose of Oxytocin in Autism: A Randomized Controlled Trial

Background

Autism spectrum disorder (ASD) is characterized by difficulties in social communication and interaction, which have been related to atypical neural processing of rewards, especially in the social domain. As intranasal oxytocin has been shown to modulate activation of the brain’s reward circuit, oxytocin might ameliorate the processing of social rewards in ASD and thus improve social difficulties.

Methods

In this randomized, double-blind, placebo-controlled, crossover functional magnetic resonance imaging study, we examined effects of a 24-IU dose of intranasal oxytocin on reward-related brain function in 37 men with ASD without intellectual impairment and 37 age- and IQ-matched control participants. Participants performed an incentive delay task that allows the investigation of neural activity associated with the anticipation and receipt of monetary and social rewards.

Results

Nonsignificant tests suggested that oxytocin did not influence neural processes related to the anticipation of social or monetary rewards in either group. Complementary Bayesian analyses indicated moderate evidence for a null model, relative to an alternative model. Our results were inconclusive regarding possible oxytocin effects on amygdala responsiveness to social rewards during reward consumption. There were no significant differences in reward-related brain function between the two groups under placebo.

Conclusions

Our results do not support the hypothesis that intranasal oxytocin generally enhances activation of reward-related neural circuits in men with and without ASD.

Is the Combination of ADOS and ADI-R Necessary to Classify ASD? Rethinking the "Gold Standard" in Diagnosing ASD

Diagnosing autism spectrum disorder (ASD) requires extensive clinical expertise and training as well as a focus on differential diagnoses. The diagnostic process is particularly complex given symptom overlap with other mental disorders and high rates of co-occurring physical and mental health concerns. The aim of this study was to conduct a data-driven selection of the most relevant diagnostic information collected from a behavior observation and an anamnestic interview in two clinical samples of children/younger adolescents and adolescents/adults with suspected ASD. Via random forests, the present study discovered patterns of symptoms in the diagnostic data of 2310 participants (46% ASD, 54% non-ASD, age range 4-72 years) using data from the combined Autism Diagnostic Observation Schedule (ADOS) and Autism Diagnostic Interview-Revised (ADI-R) and ADOS data alone. Classifiers built on reduced subsets of diagnostic features yield satisfactory sensitivity and specificity values. For adolescents/adults specificity values were lower compared to those for children/younger adolescents. The models including ADOS and ADI-R data were mainly built on ADOS items and in the adolescent/adult sample the classifier including only ADOS items performed even better than the classifier including information from both instruments. Results suggest that reduced subsets of ADOS and ADI-R items may suffice to effectively differentiate ASD from other mental disorders. The imbalance of ADOS and ADI-R items included in the models leads to the assumption that, particularly in adolescents and adults, the ADI-R may play a lesser role than current behavior observations.

Identification of the most indicative and discriminative features from diagnostic instruments for children with autism

Background

Diagnosing autism spectrum disorder (ASD) is complex and time-consuming. The present work systematically examines the importance of items from the Autism Diagnostic Interview-Revised (ADI-R) and Autism Diagnostic Observation Schedule (ADOS) in discerning children with and without ASD. Knowledge of the most discriminative features and their underlying concepts may prove valuable for the future training tools that assist clinicians to substantiate or extenuate a suspicion of ASD in nonverbal and minimally verbal children.

Methods

In two samples of nonverbal (N = 466) and minimally verbal (N = 566) children with ASD (N = 509) and other mental disorders or developmental delays (N = 523), we applied random forests (RFs) to (i) the combination of ADI-R and ADOS data versus (ii) ADOS data alone. We compared the predictive performance of reduced feature models against outcomes provided by models containing all features.

Results

For nonverbal children, the RF classifier indicated social orientation to be most powerful in differentiating ASD from non-ASD cases. In minimally verbal children, we find language/speech peculiarities in combination with facial/nonverbal expressions and reciprocity to be most distinctive.

Conclusion

Based on machine learning strategies, we carve out those symptoms of ASD that prove to be central for the differentiation of ASD cases from those with other developmental or mental disorders (high specificity in minimally verbal children). These core concepts ought to be considered in the future training tools for clinicians.

An intelligent Bayesian hybrid approach to help autism diagnosis

This paper proposes a Bayesian hybrid approach based on neural networks and fuzzy systems to construct fuzzy rules to assist experts in detecting features and relations regarding the presence of autism in human beings. The model proposed in this paper works with a database generated through mobile devices that deals with diagnoses of autistic characteristics in human beings who answer a series of questions in a mobile application. The Bayesian model works with the construction of Gaussian fuzzy neurons in the first and logical neurons in the second layer of the model to form a fuzzy inference system connected to an artificial neural network that activates a robust output neuron. The new fuzzy neural network model was compared with traditional state-of-the-art machine learning models based on high-dimensional based on real-world data sets comprising the autism occurrence in children, adults, and adolescents. The results (97.73- Children/94.32-Adolescent/97.28-Adult) demonstrate the efficiency of our new method in determining children, adolescents, and adults with autistic traits (being among the top performers among all ML models tested), can generate knowledge about the dataset through fuzzy rules.

Special educational support in children and adolescents with Autism Spectrum Disorder in Germany: Results from a parent survey

OBJECTIVE

Children and adolescents with Autism Spectrum Disorder (ASD) often receive special educational support (SES). This study aimed to evaluate SES prevalence in children and adolescents with ASD in Germany.

METHODS

A mail survey was distributed to the caregivers of 637 children and adolescents recruited at three German ASD outpatient clinics.

RESULTS

Among the 211 respondents (response: 33.1 %), 82.5 % were provided with a special educational needs statement, and 63.9 % received special education, most of them attending a public special school (57.9 %). The most frequently indicated additional support was a classroom assistant (69.0 %), followed by smaller learning groups (31.7 %). Special education was less frequently provided to individuals with Asperger syndrome than to those with childhood or atypical autism (36.0 %, 76.1 %, and 63.4 %, respectively). Using logistic regression analysis, receiving special education was significantly associated with lower IQ (<85) (Odds Ratio (OR): 8.72; 95 % confidence interval (CI): 3.41-22.32) and younger age (≤11 years, OR: 2.87; 95 % CI: 1.11-7.38), but not with ASD symptom severity.

CONCLUSIONS

The majority of children and adolescents with ASD received SES, indicating a satisfactory supply of such services in Germany. The finding that lower IQ but not ASD symptom severity predicted access to SES raises questions about the specificity of the used selection criteria.

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

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.

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

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.

Internalised stigma in adults with autism: A German multi-center survey

The aim of this study was to evaluate the extent of internalised stigma and possible predictors in adults with a diagnosis of autism spectrum disorder (ASD). We measured internalised stigma in a sample of 149 adults with ASD and an IQ ≥70 (79.2% male, mean age 31.8 years), using the Brief Version of the Internalized Stigma of Mental Illness Scale (ISMI-10). The mean ISMI-10 score was 1.93 (SD=0.57), with 15.4% of participants reporting moderate or severe internalised stigma. Moderate or severe stigma was more frequent in persons aged ≥35 years (OR: 4.36), and in individuals with low educational level (OR: 6.00). IQ, sex and ASD diagnostic subtype (ICD-10) did not influence stigma severity. Compared to other mental disorders, the level of internalised stigma in adults with ASD without intellectual disability appears to be lower.

Pathways to a diagnosis of autism spectrum disorder in Germany: a survey of parents

BACKGROUND

Early identification of autism spectrum disorders (ASD) is a prerequisite for access to early interventions. Although parents often note developmental atypicalities during the first 2 years of life, many children with ASD are not diagnosed until school age. For parents, the long period between first parental concerns and diagnosis is often frustrating and accompanied by uncertainty and worry.

METHODS

This study retrospectively explored the trajectories of children with a confirmed ASD diagnosis during the diagnostic process, from first parental concerns about their child's development until the definite diagnosis. A survey concerning the diagnostic process was distributed to parents or legal guardians of children with ASD from three specialized ASD outpatient clinics in Germany.

RESULTS

The response rate was 36.9%, and the final sample consisted of carers of 207 affected children (83.6% male, mean age 12.9 years). The children had been diagnosed with childhood autism (55.6%), Asperger syndrome (24.2%), or atypical autism (20.3%). On average, parents had first concerns when their child was 23.4 months old, and an ASD diagnosis was established at a mean age of 78.5 months. Children with atypical autism or Asperger syndrome were diagnosed significantly later (83.9 and 98.1 months, respectively) than children with childhood autism (68.1 months). Children with an IQ < 85 were diagnosed much earlier than those with an IQ ≥ 85. On average, parents visited 3.4 different health professionals (SD = 2.4, range 1-20, median: 3.0) until their child received a definite ASD diagnosis. Overall, 38.5% of carers were satisfied with the diagnostic process.

CONCLUSIONS

In this sample of children with ASD in Germany, the time to diagnosis was higher than in the majority of other comparable studies. These results flag the need for improved forms of service provision and delivery for suspected cases of ASD in Germany.

Neural mechanisms of affective matching across faces and scenes

The emotional matching paradigm, introduced by Hariri and colleagues in 2000, is a widely used neuroimaging experiment that reliably activates the amygdala. In the classic version of the experiment faces with negative emotional expression and scenes depicting distressing events are compared with geometric shapes instead of neutral stimuli of the same category (i.e. faces or scenes). This makes it difficult to clearly attribute amygdala activation to the emotional valence and not to the social content. To improve this paradigm, we conducted a functional magnetic resonance imaging study in which emotionally neutral and, additionally, positive stimuli within each stimulus category (i.e. faces, social and non-social scenes) were included. These categories enabled us to differentiate the exact nature of observed effects in the amygdala. First, the main findings of the original paradigm were replicated. Second, we observed amygdala activation when comparing negative to neutral stimuli of the same category. However, for negative faces, the amygdala response habituated rapidly. Third, positive stimuli were associated with widespread activation including the insula and the caudate. This validated adaption study enables more precise statements on the neural activation underlying emotional processing. These advances may benefit future studies on identifying selective impairments in emotional and social stimulus processing.

Complementary and alternative medicine use in adults with autism spectrum disorder in Germany: results from a multi-center survey

BACKGROUND

Complementary and Alternative Medicine (CAM) is widely used both in the general population and for the treatment of somatic and psychiatric disorders. Studies on CAM use among patients with autism spectrum disorder (ASD) have so far only focused on children and adolescents. The aim of this study was to investigate patterns of CAM use among adults with ASD.

METHODS

A questionnaire survey concerning current and lifetime use of CAM was distributed to adults with ASD between November 2015 and June 2016. Participants diagnosed by experienced clinicians using the current diagnostic gold standard were recruited from four ASD outpatient clinics in Germany. Questionnaire data was then linked to supplementary clinical data.

RESULTS

The final sample consisted of 192 adults (response: 26.8%) with a mean age of 31.5 years (80% male; diagnoses: Asperger's syndrome (58%), childhood autism (27%), atypical autism (12%)). 45% of the respondents stated that they were currently using or had used at least one CAM modality in their life. Among the participants with lifetime CAM use, almost half had used two or more different types of CAM. Alternative medical systems (e.g. homeopathy, acupuncture) were most frequently used, followed by mind-body interventions (e.g. yoga, biofeedback, animal assisted therapy). Overall, 20% of respondents stated that they would like to try at least one listed CAM modality in the future.

CONCLUSIONS

This is the first study on CAM use in adults with ASD, demonstrating considerable CAM use in this population. Given the popularity of CAM, patients should be informed about the effectiveness and potentially dangerous side effects of CAM treatments, as evidence for the majority of CAM methods in ASD is still limited.

Willingness to try and lifetime use of complementary and alternative medicine in children and adolescents with autism spectrum disorder in Germany: A survey of parents

Regardless of their limited evidence and potential adverse effects, use of complementary and alternative medicine is common in children with autism spectrum disorder. Nevertheless, data on complementary and alternative medicine use in children with autism spectrum disorder in Germany are lacking. Therefore, a questionnaire survey on the use of complementary and alternative medicine was distributed to parents of children with autism spectrum disorder from three academic autism spectrum disorder outpatient clinics in Germany. Of 211 respondents, 46% stated that their child currently used or had ever used some form of complementary and alternative medicine in their life. The complementary and alternative medicine modalities most frequently used were manipulative and body-based methods (e.g. craniosacral therapy). And 18% of caregivers expressed willingness to try complementary and alternative medicine treatments for their child with autism spectrum disorder in the future, with mind–body interventions predominating. Health professionals should be aware of the considerable complementary and alternative medicine use prevalence among children with autism spectrum disorder and offer parents information about its effectiveness and potential side effects.

On Becoming Trauma-Informed: Role of the Adverse Childhood Experiences Survey in Tertiary Child and Adolescent Mental Health Services and the Association with Standard Measures of Impairment and Severity

CONTEXT

There is a movement toward trauma-informed, trauma-focused psychiatric treatment.

OBJECTIVE

To examine Adverse Childhood Experiences (ACE) survey items by sex and by total scores by sex vs clinical measures of impairment to examine the clinical utility of the ACE survey as an index of trauma in a child and adolescent mental health care setting.

DESIGN

Descriptive, polychoric factor analysis and regression analyses were employed to analyze cross-sectional ACE surveys (N = 2833) and registration-linked data using past admissions (N = 10,400) collected from November 2016 to March 2017 related to clinical data (28 independent variables), taking into account multicollinearity.

RESULTS

Distinct ACE items emerged for males, females, and those with self-identified sex and for ACE total scores in regression analysis. In hierarchical regression analysis, the final models consisting of standard clinical measures and demographic and system variables (eg, repeated admissions) were associated with substantial ACE total score variance for females (44%) and males (38%). Inadequate sample size foreclosed on developing a reduced multivariable model for the self-identified sex group.

CONCLUSION

The ACE scores relate to independent clinical measures and system and demographic variables. There are implications for clinical practice. For example, a child presenting with anxiety and a high ACE score likely requires treatment that is different from a child presenting with anxiety and an ACE score of zero. The ACE survey score is an important index of presenting clinical status that guides patient care planning and intervention in the progress toward a trauma-focused system of care.

Amygdala and oxytocin functioning as keys to understanding and treating autism: Commentary on an RDoC based approach

The recent review by Hennessey, Andari and Rainnie (2018) utilizes the proposed Research Domain Criteria (RDoC) to classify amygdala functions and relate them to autism symptomatology. This approach has the potential to challenge the overarching autism diagnosis by furthering our knowledge of the mechanisms giving rise to autism psychopathology and generate novel treatment options. The purpose of this commentary is to provide additional information on a number of points raised in the review. Thus, (1) we discuss the issue of amygdala and brain overgrowth in children with autism and relate it to developmental oxytocin changes, (2) examine potential mechanisms that underlie amygdala overgrowth and dysfunction of the oxytocin system, (3) zoom in on the sexually dimorphic characteristics of the amygdala and potential parallels with the oxytocin system and (4) discuss how the interplay of oxytocin and vasopressin may explain the partially inconsistent findings of their effects on amygdala functioning.

A Review of the Safety, Efficacy and Mechanisms of Delivery of Nasal Oxytocin in Children: Therapeutic Potential for Autism and Prader-Willi Syndrome, and Recommendations for Future Research

In this article, we conduct a comprehensive review of existing evidence for the safety and therapeutic potential of intranasal oxytocin in pediatric populations. Unique considerations for dosing and delivery of oxytocin to the nasal passageway in pediatric populations and methods to promote adherence are reviewed. Intranasal oxytocin has been administered to 261 children in three open-label studies and eight randomized controlled trials. To date, the only published results in pediatric populations have focused on autism spectrum disorder (ASD) and Prader-Willi syndrome (PWS). Results regarding efficacy for improving social impairment in ASD are equivocal, partially due to mixed methodological designs, dosing regimens, and outcome measures. At present, there is no randomized controlled evidence that oxytocin provides benefit to individuals with PWS. There is no clear evidence of a link between oxytocin administration and any specific adverse event. Adverse events have been assessed using medical interviews, open reports, checklists, and physiological assessments. Adverse events reports have been largely classified as mild (n = 93), with few moderate (n = 9) or severe (n = 3) events reported. There were 35 additional adverse events reported, without severity ratings. Severe events, hyperactivity and irritability, occurred at first administration in both placebo and oxytocin groups, and subsided subsequent to discontinuation. We note that adverse event monitoring is inconsistent and often lacking, and reporting of its relationship to the study drug is poor. Only one study reported adherence data to suggest high adherence. Recommendations are then provided for the delivery of nasal sprays to the nasal passageway, monitoring, and reporting of efficacy, safety, and adherence for oxytocin nasal spray trials in pediatric populations.