Light Cannabis Use and the Adolescent Brain: An 8-years Longitudinal Assessment of Mental Health, Cognition, and Reward Processing.

RATIONALE: For decades, cannabis has been the most widely used illicit substance in the world, particularly among youth. Research suggests that mental health problems associated with cannabis use may result from its effect on reward brain circuit, emotional processes, and cognition. However, findings are mostly derived from correlational studies and inconsistent, particularly in adolescents. OBJECTIVES AND METHODS: Using data from the IMAGEN study, participants (non-users, persistent users, abstinent users) were classified according to their cannabis use at 19 and 22 years-old. All participants were cannabis-naïve at baseline (14 years-old). Psychopathological symptoms, cognitive performance, and brain activity while performing a Monetary Incentive Delay task were used as predictors of substance use and to analyze group differences over time. RESULTS: Higher scores on conduct problems and lower on peer problems at 14 years-old (n = 318) predicted a greater likelihood of transitioning to cannabis use within 5 years. At 19 years of age, individuals who consistently engaged in low-frequency (i.e., light) cannabis use (n = 57) exhibited greater conduct problems and hyperactivity/inattention symptoms compared to non-users (n = 52) but did not differ in emotional symptoms, cognitive functioning, or brain activity during the MID task. At 22 years, those who used cannabis at both 19 and 22 years-old n = 17), but not individuals that had been abstinent for ≥ 1 month (n = 19), reported higher conduct problems than non-users (n = 17). CONCLUSIONS: Impairments in reward-related brain activity and cognitive functioning do not appear to precede or succeed cannabis use (i.e., weekly, or monthly use). Cannabis-naïve adolescents with conduct problems and more socially engaged with their peers may be at a greater risk for lighter yet persistent cannabis use in the future.

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.

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.

The future of General Movement Assessment: The role of computer vision and machine learning - A scoping review.

BACKGROUND: The clinical and scientific value of Prechtl general movement assessment (GMA) has been increasingly recognised, which has extended beyond the detection of cerebral palsy throughout the years. With advancing computer science, a surging interest in developing automated GMA emerges. AIMS: In this scoping review, we focused on video-based approaches, since it remains authentic to the non-intrusive principle of the classic GMA. Specifically, we aimed to provide an overview of recent video-based approaches targeting GMs; identify their techniques for movement detection and classification; examine if the technological solutions conform to the fundamental concepts of GMA; and discuss the challenges of developing automated GMA. METHODS AND PROCEDURES: We performed a systematic search for computer vision-based studies on GMs. OUTCOMES AND RESULTS: We identified 40 peer-reviewed articles, most (n = 30) were published between 2017 and 2020. A wide variety of sensing, tracking, detection, and classification tools for computer vision-based GMA were found. Only a small portion of these studies applied deep learning approaches. A comprehensive comparison between data acquisition and sensing setups across the reviewed studies, highlighting limitations and advantages of each modality in performing automated GMA is provided. CONCLUSIONS AND IMPLICATIONS: A "method-of-choice" for automated GMA does not exist. Besides creating large datasets, understanding the fundamental concepts and prerequisites of GMA is necessary for developing automated solutions. Future research shall look beyond the narrow field of detecting cerebral palsy and open up to the full potential of applying GMA to enable an even broader application.

Toward a Dimensional Assessment of Externalizing Disorders in Children: Reliability and Validity of a Semi-Structured Parent Interview.

OBJECTIVE: This study assesses the reliability and validity of the DSM-5-based, semi-structured Clinical Parent Interview for Externalizing Disorders in Children and Adolescents (ILF-EXTERNAL). METHOD: Participant data were drawn from the ongoing ESCAschool intervention study. The ILF-EXTERNAL was evaluated in a clinical sample of 474 children and adolescents (aged 6-12 years, 92 females) with symptoms of attention-deficit/hyperactivity disorder (ADHD). To obtain interrater reliability, the one-way random-effects, absolute agreement models of the intraclass correlation (ICC) for single ICC(1,1) and average measurements ICC(1,3) were computed between the interviewers and two independent raters for 45 randomly selected interviews involving ten interviewers. Overall agreement on DSM-5 diagnoses was assessed using Fleiss' kappa. Further analyses evaluated internal consistencies, item-total correlations as well as correlations between symptom severity and the degree of functional impairment. Additionally, parents completed the German version of the Child Behavior Checklist (CBCL) and two DSM-5-based parent questionnaires for the assessment of ADHD symptoms and symptoms of disruptive behavior disorders (FBB-ADHS; FBB-SSV), which were used to evaluate convergent and divergent validity. RESULTS: ICC coefficients demonstrated very good to excellent interrater reliability on the item and scale level of the ILF-EXTERNAL [scale level: ICC(1,1) = 0.83-0.95; ICC(1,3) = 0.94-0.98]. Overall kappa agreement on DSM-5 diagnoses was substantial to almost perfect for most disorders (0.38 ≤ κ ≤ 0.94). With some exceptions, internal consistencies (0.60 ≤ α ≤ 0.86) and item-total correlations (0.21 ≤ r it ≤ 0.71) were generally satisfactory to good. Furthermore, higher symptom severity was associated with a higher degree of functional impairment. The evaluation of convergent validity revealed positive results regarding clinical judgment and parent ratings (FBB-ADHS; FBB-SSV). Correlations between the ILF-EXTERNAL scales and the CBCL Externalizing Problems were moderate to high. Finally, the ILF-EXTERNAL scales were significantly more strongly associated with the CBCL Externalizing Problems than with the Internalizing Problems, indicating divergent validity. CONCLUSION: In clinically referred, school-age children, the ILF-EXTERNAL demonstrates sound psychometric properties. The ILF-EXTERNAL is a promising clinical interview and contributes to high-quality diagnostics of externalizing disorders in children and adolescents.

Cognitive and brain development is independently influenced by socioeconomic status and polygenic scores for educational attainment.

Genetic factors and socioeconomic status (SES) inequalities play a large role in educational attainment, and both have been associated with variations in brain structure and cognition. However, genetics and SES are correlated, and no prior study has assessed their neural associations independently. Here we used a polygenic score for educational attainment (EduYears-PGS), as well as SES, in a longitudinal study of 551 adolescents to tease apart genetic and environmental associations with brain development and cognition. Subjects received a structural MRI scan at ages 14 and 19. At both time points, they performed three working memory (WM) tasks. SES and EduYears-PGS were correlated (r = 0.27) and had both common and independent associations with brain structure and cognition. Specifically, lower SES was related to less total cortical surface area and lower WM. EduYears-PGS was also related to total cortical surface area, but in addition had a regional association with surface area in the right parietal lobe, a region related to nonverbal cognitive functions, including mathematics, spatial cognition, and WM. SES, but not EduYears-PGS, was related to a change in total cortical surface area from age 14 to 19. This study demonstrates a regional association of EduYears-PGS and the independent prediction of SES with cognitive function and brain development. It suggests that the SES inequalities, in particular parental education, are related to global aspects of cortical development, and exert a persistent influence on brain development during adolescence.

[The diagnostics of autism spectrum disorder in children, adolescents and adults: Overview of the key questions and main results of the first part of the German AWMF-S3 - clinical guideline]. / Diagnostik von Autismus- Spektrum-Störungen im Kindes-, Jugend- und Erwachsenenalter: Überblick zu den wesentlichen Fragestellungen und Ergebnissen des ersten Teils der S3-Leitlinie.

The diagnostics of autism spectrum disorder in children, adolescents and adults: Overview of the key questions and main results of the first part of the German AWMF-S3 - clinical guideline Abstract. Background: Autism spectrum disorders (ASD) include ICD-10 diagnoses of childhood autism, Asperger syndrome, and atypical autism; there is a lifetime prevalence of ~1 %. The aim of the evidence-based clinical guideline (AWMF-S3-Guideline) is to summarize the current evidence concerning diagnostic and therapeutic processes for professionals working in healthcare and social welfare and to provide consensus on clinical recommendations. The present study summarizes the most important results of the diagnostic part of this guideline. Method: The guideline group comprised 14 clinical and scientific expert associations from the German healthcare system, in addition to representatives of relatives and patients. Recommendations were based on results of a systematic literature search, data extraction, the evaluation of study quality, and, if possible, meta-analytic aggregation of included data in combination with the clinical expertise of the respective representatives. Consensus-based recommendations were determined via nominal group technique. Results: The AWMF-S3-Clinical Guideline, Diagnostic Part, summarizes current research on this topic. The main focus is put on the question of obligatory versus redundant diagnostic procedures. After a general introduction to the clinical picture of ASD, essential aspects like obtaining the medical history, the effective use of screening and diagnostic instruments, medical examination, the full diagnostic work-up as well as communicating the diagnostic results to relatives and patients are described in detail. We also conducted a meta-analysis on the stability of early diagnosis. Conclusion: This first part of the ASD guideline offers users the opportunity to inform themselves about the background of ASD as well as evidence-based and broadly consented information on the correct diagnostic process of ASD from infancy to adulthood.

Validation of the Movie for the Assessment of Social Cognition in Adolescents with ASD: Fixation Duration and Pupil Dilation as Predictors of Performance.

Impaired social cognition is one of the core characteristics of autism spectrum disorders (ASD). Appropriate measures of social cognition for high-functioning adolescents with ASD are, however, lacking. The Movie for the Assessment of Social Cognition (MASC) uses dynamic social stimuli, ensuring ecological validity, and has proven to be a sensitive measure in adulthood. In the current study, 33 adolescents with ASD and 23 controls were administered the MASC, while concurrent eye tracking was used to relate gaze behavior to performance levels. The ASD group exhibited reduced MASC scores, with social cognition performance being explained by shorter fixation duration on eyes and decreased pupil dilation. These potential diagnostic markers are discussed as indicators of different processing of social information in ASD.

Child impact on family functioning: a multivariate analysis in multiplex families with children and mothers both affected by attention-deficit/hyperactivity disorder (ADHD).

ADHD seriously impacts family functioning, even the more in families with simultaneous parental and child ADHD. The aim of the study was to examine associations between family impact of child ADHD and child, mother and family characteristics in multiplex families with children and mothers both affected by ADHD. One hundred and forty-four mother-child pairs were assessed (children: mean age 9.4 ± 1.7 years, 73.6 % male). Family impact of child ADHD was rated by mothers using the Family Impact Questionnaire (FIQ). Multiple linear regression analyses were performed with child and maternal psychopathology and basic family characteristics such as employment, partnership status and number of children as predictors and FIQ subscores as criteria. Rates of variance explained by family variables were 49 % for negative feelings towards the child, 37 % for impact on partnership, 31 % for impact on social life and 27 % for impact on finances (p < .001, respectively). Pearson correlations with family impact were especially strong for child externalizing symptoms, maternal ADHD and co-morbid symptoms of the mother. The strongest independent predictor was oppositional defiant child behaviour. In ADHD multiplex families, mothers' perception of the impact of an ADHD child on its family can be explained to a substantial degree by child psychopathology, maternal psychopathology and basic family characteristics. Although a cross-sectional design does not allow for causal interpretations, the findings of this study offer important targets for the treatment of ADHD in a family context pointing to the need for assessing and treating parental mental health and co-morbid symptoms besides ADHD core symptoms.

Impact of ADHD symptoms on autism spectrum disorder symptom severity.

Despite the official exclusion criteria for autism spectrum disorder (ASD) and attention deficit/hyperactivity disorder (ADHD) in the DSM-IV and ICD-10, patients with ASD often show ADHD symptoms. We aimed to examine the potential influence of ADHD symptoms on autistic psychopathology in a large sample of patients with ASD. We tested the hypothesis that patients with ASD and an additional ADHD (ASD+) would show a higher severity of autistic symptoms than those with ASD only (ASD-). We measured autistic symptoms using the autism diagnostic observation schedule (ADOS-G), the autism diagnostic interview (ADI-R), and the social responsiveness scale (SRS). To measure overall psychopathology and ADHD symptoms, we used the child behavior checklist (CBCL) and the ADHD rating scale (FBB-ADHS), respectively. Group differences between the ASD+ and the ASD- group (group division was conducted according to the results of the FBB-ADHS) were calculated using a univariate analysis of variance (ANOVA). The ASD+ group showed a greater severity of autistic symptoms than the ASD- group, measured by the SRS and the ADI-R. Especially in the social interaction subscale (ADI-R), a significantly higher symptom severity was found in the ASD+ group. No significant group differences were found regarding autistic symptoms measured by the ADOS-G. Patients with ASD and an additional ADHD expressed a stronger severity of autistic symptoms than patients with ASD only. According to our results, the possibility of a co-diagnosis of ADS and ADHD, as is being planned in the DSM-5, is in line with earlier studies, is highly reasonable, will simplify research, and have therapeutic implications.