1. Alkinj I, Pereira A, Santos P. The effects of an educational program based on modeling and social stories on improvements in the social skills of students with autism. Heliyon. 2022; 8(5): e09289.

Social communication difficulties are one of the most common issues among individuals with autism spectrum disorder (ASD), as ASD affects their social and academic lives and isolates them from their environment. Several studies that utilized video modeling, video self-modeling, or social stories (or social stories combined with video modeling) have yielded promising outcomes in improving the social skills of individuals with ASD. However, to date, the effects of the combination of all three strategies have not been studied. The current study aimed to examine the effectiveness of an educational program based on multiple strategies, including social stories, animated video modeling, and video self-modeling, to improve the social communication skills of a sample of six high-functioning students with ASD at the Autism Academy of Jordan. A mixed method (quantitative and qualitative) approach was used to examine the impact of the program on the experimental group. The results of the Mann-Whitney test indicated that compared to the monitoring group, all participants in the experimental group achieved significant improvements in the post-test of the Autism Social Skills Profile in both the domains of social reciprocity and social participation skills. Furthermore, the data from teachers’ interviews, analyzed using WebQDA software, corroborated the results in terms of significant improvements in students’ social skills after the implementation of the educational program. The implications of the study for psychological and educational interventions are addressed, and research suggestions are made to promote the personal and social development of individuals with ASD.

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2. Bemmouna D, Weibel S, Kosel M, Hasler R, Weiner L, Perroud N. The utility of the autism-spectrum quotient to screen for autism spectrum disorder in adults with attention deficit/hyperactivity disorder. Psychiatry research. 2022; 312: 114580.

Co-occurring attention deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) has been reported to be highly prevalent in adults. However, very few studies have assessed the usefulness of screening instruments to detect this co-occurrence, particularly when screening for ASD in the context of ADHD. Our study aimed at assessing the utility of the autism-spectrum quotient (AQ) as a screening tool of ASD in a sample of 153 adults referred for ADHD assessment. Our results showed that the AQ is of limited use in this context as its positive predictive value was low (47%). Particularly, the more severe the attentional deficits the more likely individuals with ADHD were to be misclassified as having a co-occurring ASD based on the AQ. However, the « imagination » subscale of the AQ was able to discriminate those who met ASD criteria from those who did not, suggesting that targeting imagination impairments might be useful when assessing for the ADHD+ASD co-occurrence in clinical settings.

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3. Cao P, Wen G, Liu X, Yang J, Zaiane OR. Modeling the dynamic brain network representation for autism spectrum disorder diagnosis. Medical & biological engineering & computing. 2022.

The dynamic functional connectivity analysis provides valuable information for understanding functional brain activity underlying different cognitive processes. Modeling spatio-temporal dynamics in functional brain networks is critical for underlying the functional mechanism of autism spectrum disorder (ASD). In our study, we propose a machine learning approach for the classification of neurological disorders while providing an interpretable framework, which thoroughly captures spatio-temporal features in resting-state functional magnetic resonance imaging (rs-fMRI) data. Specifically, we first transform rs-fMRI time-series into temporal multi-graph using the sliding window technique. A temporal multi-graph clustering is then designed to eliminate the inconsistency of the temporal multi-graph series. Then, a graph structure-aware LSTM (GSA-LSTM) is further proposed to capture the spatio-temporal embedding for temporal graphs. Furthermore, The proposed GSA-LSTM can not only capture discriminative features for prediction but also impute the incomplete graphs for the temporal multi-graph series. Extensive experiments on the autism brain imaging data exchange (ABIDE) dataset demonstrate that the proposed dynamic brain network embedding learning outperforms the state-of-the-art brain network classification models. Furthermore, the obtained clustering results are consistent with the previous neuroimaging-derived evidence of biomarkers for autism spectrum disorder (ASD).

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4. Chen Y, Zhou Z, Cao M, Liu M, Lin Z, Yang W, Yang X, Dhaidhai D, Xiong P. Extended Reality (XR) and Telehealth Interventions for Children or Adolescents with Autism Spectrum Disorder: Systematic Review of Qualitative and Quantitative Studies. Neuroscience and biobehavioral reviews. 2022: 104683.

World Health Organization reported that almost one in 100 children is diagnosed with autism spectrum disorder (ASD) worldwide. Extended Reality (XR) and Telehealth interventions are evident to be effective for ASD treatments. While there is no comprehensive systematic review to summarize and evaluate the evidence for promoting the accessibility of different technology-based treatment regiments. This paper aims to verify the efficacy and validity of XR and Telehealth interventions for children and adolescents with ASD. We reviewed 112 studies from databases of PubMed, Web of Science and Cochrane Library, published in English between January 2010 to April 1(st), 2022. We found that after interventions, positive improvements for ASD participants were observed in social interaction, acceptance, and engagement, communication and speech, emotion recognition and control, daily living skill, problem behavior reduction, attention, cost reduction, anxiety symptom reduction, pretend play, contextual processing, match to sample skill, and insomnia control. Our findings provide a solid and positive evidence of XR and Telehealth interventions in improving the treatment outcomes for children and adolescents with ASD. In the future, more research with RCTs and standardized outcome measurements are required to establish the therapeutic efficiency of the two interventions independently or combined.

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5. Eroğlu Y, Baykara M, Perçinel Yazici İ, Utku Yazici K, Kürşad Poyraz A. Evaluation of the corpus callosum using magnetic resonance imaging histogram analysis in autism spectrum disorder. The neuroradiology journal. 2022: 19714009221097507.

BACKGROUND: Histogram analysis is a texture analysis method that can be used in medical images. Quantitative values of the intensity of images can be obtained with histogram analysis. It aimed to evaluate corpus callosum in magnetic resonance images (MRIs) using histogram analysis of pediatric patients with autism spectrum disorder (ASD) to compare them with healthy controls. METHODS: This study included 29 children with ASD and 29 healthy children with normal brain MRI. High-resolution three-dimensional turbo field echo images were obtained with a 1.5 T scanner device for brain magnetic resonance imaging. On the corpus callosum in the sagittal T1-weighted images obtained, mean gray level density (mean), the standard deviation, median, minimum, maximum, entropy, variance, skewness, kurtosis, uniformity, size % L, size % M, size % U, and percentile parameters were measured. RESULTS: In ASD patients, mean, standard deviation, maximum, median, variance, entropy, 25%, 75%, 90%, 97%, and 99% values were found to be lower than the control group, and size % U value was higher. In addition, the corpus callosum area was significantly lower in the ASD compared to the controls. CONCLUSION: According to our study, corpus callosum of patients with ASD showed differences compared to healthy controls by histogram analysis, even though they were seen as normal in brain MRI. We think that histogram analysis can be used to evaluate possibly affected areas of brain in ASD patients.

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6. Freitas C, Hunt BAE, Wong SM, Ristic L, Fragiadakis S, Chow S, Iaboni A, Brian J, Soorya L, Chen JL, Schachar R, Dunkley BT, Taylor MJ, Lerch JP, Anagnostou E. Atypical Functional Connectivity During Unfamiliar Music Listening in Children With Autism. Frontiers in neuroscience. 2022; 16: 829415.

BACKGROUND: Atypical processing of unfamiliar, but less so familiar, stimuli has been described in Autism Spectrum Disorder (ASD), in particular in relation to face processing. We examined the construct of familiarity in ASD using familiar and unfamiliar songs, to investigate the link between familiarity and autism symptoms, such as repetitive behavior. METHODS: Forty-eight children, 24 with ASD (21 males, mean age = 9.96 years ± 1.54) and 24 typically developing (TD) controls (21 males, mean age = 10.17 ± 1.90) completed a music familiarity task using individually identified familiar compared to unfamiliar songs, while magnetoencephalography (MEG) was recorded. Each song was presented for 30 s. We used both amplitude envelope correlation (AEC) and the weighted phase lag index (wPLI) to assess functional connectivity between specific regions of interest (ROI) and non-ROI parcels, as well as at the whole brain level, to understand what is preserved and what is impaired in familiar music listening in this population. RESULTS: Increased wPLI synchronization for familiar vs. unfamiliar music was found for typically developing children in the gamma frequency. There were no significant differences within the ASD group for this comparison. During the processing of unfamiliar music, we demonstrated left lateralized increased theta and beta band connectivity in children with ASD compared to controls. An interaction effect found greater alpha band connectivity in the TD group compared to ASD to unfamiliar music only, anchored in the left insula. CONCLUSION: Our results revealed atypical processing of unfamiliar songs in children with ASD, consistent with previous studies in other modalities reporting that processing novelty is a challenge for ASD. Relatively typical processing of familiar stimuli may represent a strength and may be of interest to strength-based intervention planning.

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7. Lee IO, Skuse DH, Constable PA, Marmolejo-Ramos F, Olsen LR, Thompson DA. The electroretinogram b-wave amplitude: a differential physiological measure for Attention Deficit Hyperactivity Disorder and Autism Spectrum Disorder. Journal of neurodevelopmental disorders. 2022; 14(1): 30.

BACKGROUND: Attention Deficit Hyperactivity Disorder (ADHD) is the most prevalent childhood neurodevelopmental disorder. It shares some genetic risk with Autism Spectrum Disorder (ASD), and the conditions often occur together. Both are potentially associated with abnormal glutamate and GABA neurotransmission, which can be modelled by measuring the synaptic activity in the retina with an electroretinogram (ERG). Reduction of retinal responses in ASD has been reported, but little is known about retinal activity in ADHD. In this study, we compared the light-adapted ERGs of individuals with ADHD, ASD and controls to investigate whether retinal responses differ between these neurodevelopmental conditions. METHODS: Full field light-adapted ERGs were recorded from 15 ADHD, 57 ASD (without ADHD) and 59 control participants, aged from 5.4 to 27.3 years old. A Troland protocol was used with a random series of nine flash strengths from -0.367 to 1.204 log photopic cd.s.m(-2). The time-to-peak and amplitude of the a- and b-waves and the parameters of the Photopic Negative Response (PhNR) were compared amongst the three groups of participants, using generalised estimating equations. RESULTS: Statistically significant elevations of the ERG b-wave amplitudes, PhNR responses and faster timings of the b-wave time-to-peak were found in those with ADHD compared with both the control and ASD groups. The greatest elevation in the b-wave amplitudes associated with ADHD were observed at 1.204 log phot cd.s.m(-2) flash strength (p < .0001), at which the b-wave amplitude in ASD was significantly lower than that in the controls. Using this measure, ADHD could be distinguished from ASD with an area under the curve of 0.88. CONCLUSIONS: The ERG b-wave amplitude appears to be a distinctive differential feature for both ADHD and ASD, which produced a reversed pattern of b-wave responses. These findings imply imbalances between glutamate and GABA neurotransmission which primarily regulate the b-wave formation. Abnormalities in the b-wave amplitude could provisionally serve as a biomarker for both neurodevelopmental conditions.

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8. Pathak A, Mobin N, Prasad KN, Mondal K, Mitra O, Kumar A, Sinha H. To assess the magnitude of autism spectrum disorder in Jharkhand by M-CHAT-R as a screening tool. Journal of family medicine and primary care. 2022; 11(4): 1497-501.

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder which is a clinically heterogenous condition with a wide range of etiological factors and causing significant public health burden. If diagnosed at an earlier age, early interventions can be started this leads to functional outcome of children with ASD with respect to social, behavior and occupational sphere. Therefore, early detection and intervention are widely recommended in these children. So screening of toddlers who were identified to be « at risk » can be diagnosed using screening questionnaires by interviewing parents. Overall with this study we can conclude that, toddlers identified to be « at risk » and those diagnosed with ASD were not uncommon and M-CHAT-R is a useful screening test for the identification of « at risk » toddlers for Autism Spectrum Disorder in Jharkhand.

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9. Pickles K. Call for autistic vets to complete workplace survey. The Veterinary record. 2022; 190(9): 373.

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10. Sacrey LR, Zwaigenbaum L, Bryson SE, Brian JA, Smith IM, Garon N, Vaillancourt T, Roncadin C. Temperament in Infancy Predicts Internalizing and Externalizing Problem Behavior at Age 5 in Children With an Increased Likelihood of Autism Spectrum Disorder. Frontiers in psychology. 2022; 13: 816041.

Differences in temperament have been linked to later mental health. Children with autism spectrum disorder (ASD) have an increased likelihood of experiencing such problems, including anxiety, depression, attention deficit/hyperactivity disorder, and oppositional defiant disorder; yet, relations between early temperament and later mental health are not well understood. In this paper, we assess the relationship between temperament in infancy and internalizing and externalizing behavior at age 5, in 178 children at an increased likelihood of being diagnosed with ASD (i.e., younger siblings of children with ASD). Temperament was assessed using the parent-reported Infant Behavior Questionnaire (IBQ) at 6 and 12 months of age and the Toddler Behavior Assessment Questionnaire-Revised (TBAQ-R) at 24 months of age. Mental health problems were assessed using the parent-reported Child Behavior Checklist (CBCL) at age 5. The data were analyzed using hierarchical multiple regressions, with individual temperament subscale scores as single predictor variables (Subscale Score) or temperament profiles using confirmatory factor analyses (Person-Centered Profile) in the first block, Autism Diagnostic Observation Schedule total severity scores at age 3 in the second block, and expressive and receptive language scores (from Mullen Scales of Early Learning) at age 3 in the third block for each model. Three main findings were: (1) 4 of 6 IBQ subscales at both 6 and 12 months significantly predicted internalizing and externalizing problems at age 5; (2) 9 and 8 of 13 TBAQ-R subscales at 24 months significantly predicted internalizing and externalizing problems, respectively, at age 5; and (3) a « sticky attention » temperament profile significantly predicted internalizing problems, whereas a « low-focused » profile significantly predicted externalizing problems, both at age 5. The results of this study support the supposition that temperament is a trans-diagnostic risk factor for later mental health conditions. Exploring temperament profiles and trajectories may illuminate early avenues for prevention in siblings of children with ASD who are at an increased likelihood of experiencing mental health problems, regardless of ASD diagnostic status.

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11. Schneider S, Clément C, Goltzene MA, Meyer N, Gras-Vincendon A, Schröder CM, Coutelle R. Determinants of the evolutions of behaviours, school adjustment and quality of life in autistic children in an adapted school setting: an exploratory study with the International Classification of Functioning, disability and health (ICF). BMC psychiatry. 2022; 22(1): 323.

BACKGROUND: Previous studies about Quality of Life (QoL) in autistic children (ASD) have put forward the negative impact of factors such as Autism Spectrum Disorder (ASD) severity, psychiatric comorbidities and adaptive behaviour impairment. However, little is known about the relation of these factors to school adjustment, measured with the International Classification of Functions disability and health (ICF) framework (World Health Organization, 2001), and QoL evolutions. Thus, this study aimed at investigating the determinants of behaviours, school adjustment and QoL changes in 32 children in an ASD inclusion program over one academic year. METHODS: Using Bayesian methods, we studied the impact of ASD severity, psychiatric comorbidities, adaptive behaviour level and a diagnosis of Pathological Demand Avoidance (PDA) on evolutions of behaviour, school adjustment (measured with the ICF) and QoL. RESULTS: As predicted, adequate adaptive behaviour levels were associated with better progress of behaviours and school adjustment whereas psychiatric comorbidities were related to worse outcome of school adjustment. Contrary to our hypotheses, severe ASD was associated to better evolution of adjustment at school. PDA was not discriminant. We did not find any association between the studied factors and the evolution of QoL over the academic year. CONCLUSION: Our results show that the assessment of adaptive behaviour levels, psychiatric comorbidities and ASD severity level may be useful predictors to discriminate of school adjustment evolution (assessed by teachers within the ICF model) over a one-year period in autistic children. The assessment of this time course of school adjustment was sensitive to change and adapted to differentiate evolutions in an inclusive education framework. The investigation of quality of school life of autistic children as well as its determinants may therefore be relevant to improving academic adaptation. However, further research in larger groups, over longer periods and in different personalized school settings for autistic children is needed.

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12. Trundle G, Jones KA, Ropar D, Egan V. Prevalence of Victimisation in Autistic Individuals: A Systematic Review and Meta-Analysis. Trauma, violence & abuse. 2022: 15248380221093689.

Autistic individuals are at an increased risk of experiencing victimisation. Previous reviews have focussed specific types of victimisation. Thus, a clearer picture considering the range of victimisation experiences autistic people face is required. This systematic review aims to identify the prevalence of victimisation in autistic individuals considering a variety of victimisation types (e.g., bulling, sexual victimisation, and crime) in both adults and children from clinical and community settings. Through systematic searches of relevant databases, 291 studies met the criteria for review. Of those, 34 studies met the inclusion criteria: a) quantitative studies, b) involving autistic individuals, c) reporting prevalence rates of victimisation. Meta-analysis found a pooled prevalence rate of victimisation of 44% in autistic individuals. Subgroup analysis examined moderating factors as high heterogeneity was present. This found the pooled prevalence rates for bullying to be 47%, 16% for child abuse, 40% for sexual victimisation, 13% for cyberbullying, and 84% for multiple forms of victimisation in autistic individuals, though heterogeneity remained. Correction for participants’ age, reporter used, and the population which the sample was recruited from did not reduce heterogeneity. Although heterogeneity impedes the definitive interpretation of the findings, this review illustrates the need for strategies and interventions to reduce the incidence of victimisation.

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13. Wang G, Chen J, Zhang K, Tang S, Wang G. The mediating role of gaze patterns in the association of child sleep disturbances and core symptoms of autism spectrum disorder. Autism research : official journal of the International Society for Autism Research. 2022.

Children with autism spectrum disorder (ASD) are at high risk for sleep disturbances, but the mechanism underlying the association between sleep disturbances and ASD core symptoms is largely unknown. This study examined the relationship between sleep disturbances and ASD core symptoms, and the mediating role of gaze patterns during the facial emotion recognition (FER) task. The study included 57 children with ASD and 59 age- and intelligence-matched typically developing (TD) controls aged 3-7 years. Parents reported their children’s sleep disturbances and ASD core symptoms using the Children’s Sleep Habits Questionnaire (CSHQ) and Social Communication Questionnaire (SCQ). Children’s gaze patterns during the FER task were recorded by an eye tracking method. We found (1) ASD children had more severe sleep disturbances than TD children; (2) ASD children had atypical gaze patterns and poor FER task performance as determined by lower accuracy and longer reaction time; (3) sleep disturbances were significantly associated with ASD core symptoms of social interaction, communication, and restricted, repetitive and stereotyped patterns of behavior; and (4) atypical gaze patterns partially mediated the association between sleep disturbances and ASD core symptoms. These findings suggest the need for more comprehensive clinical interventions and more effective sleep interventions to improve ASD core symptoms. LAY SUMMARY: Sleep disturbances are very common in children with autism spectrum disorder (ASD). The current study found that sleep disturbances were significantly associated with ASD core symptoms, and gaze patterns during facial emotion recognition task could partially mediate this relationship.

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