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Introduction: Autism Spectrum Disorders (ASD) and Obsessive Compulsive Disorders (OCD) can be confused with each other but can also occur together, presenting a more severe clinical picture with a worse response to typical OCD treatment., Objective: We review the current situation on the topic, the specific characteristics of both disorders, the implication of the changes to the DSM-5-TR, their evaluation and approach., Conclusions: ASD-OCD comorbidity presents atypicalities that require a detailed evaluation and adapted treatments.

Introduction: Pragmatics plays a crucial role in learning and socio-emotional adaptation and it is a core area of impairment in Autism Spectrum Disorder (ASD). The aim of this study is to examine the discriminant validity of the Spanish adaptation of the Language Use Inventory (LUI-Spanish), designed to assess pragmatic skills in children., Materials and Methods: The study included 40 children diagnosed with ASD and 40 typically developing (TD) children, aged between 24 and 42 months. The LUISpanish, a parent-report measure of pragmatic language, was used to assess communication through gestures, words and sentences. The Mann-Whitney U test was employed for group comparisons., Results: Statistically significant differences were found between the ASD and TD groups in most of the LUI scales, except for Part 1 and the scales included. The TD group consistently scored higher, with large effect sizes. The instrument demonstrates both theoretical and practical relevance for assessing early pragmatic skills and guiding appropriate interventions.

Autism Spectrum Disorder (ASD) encompasses a range of neurodevelopmental conditions characterized by social challenges, repetitive behaviors, and communication difficulties. While diagnosis traditionally relies on behavioral observations, new biomedical approaches, such as the Research Domain Criteria (RDoC), aim to identify biomarkers that integrate genetic, neural, and behavioral factors. Notable biomarkers include genetic variants, molecular alterations such as abnormal neurotransmitter levels, and markers associated with immune dysfunction. Brain organoids have also enabled the investigation of specific neural mechanisms. In neuroimaging, techniques such as functional magnetic resonance imaging (fMRI) and functional near-infrared spectroscopy (fNIRS) have identified atypical connectivity patterns in infants at high risk for ASD. Similarly, measures like electroencephalography (EEG) and eye tracking have revealed differences in visual attention and brain activity, while physiological indicators such as electrodermal activity (EDA) and heart rate variability (HRV) reflect sensory and autonomic dysfunctions. The use of digital biomarkers is rapidly growing, with devices like tablets and virtual reality capturing data on children's interactions. Analyzed using artificial intelligence, these data show promise for improving early ASD detection, though further validation is needed. Integrating traditional and digital approaches is essential for advancing diagnosis and intervention strategies.

Autism Spectrum Disorder (ASD) is a disorder of brain growth with great variability whose clinical presentation initially shows up during early stages or youth, and ASD follows a repetitive pattern of behavior in most cases. Accurate diagnosis of ASD has been difficult in clinical practice as there is currently no valid indicator of ASD. Since ASD is regarded as a neurodevelopmental disorder, brain signals specially electroencephalography (EEG) are an effective method for detecting ASD. Therefore, this research aims at developing a method of extracting features from EEG signal for discriminating between ASD and control subjects. This study applies six prominent connectivity features, namely Cross Correlation (XCOR), Phase Locking Value (PLV), Pearson's Correlation Coefficient (PCC), Mutual Information (MI), Normalized Mutual Information (NMI) and Transfer Entropy (TE), for feature extraction. The Connectivity Feature Maps (CFMs) are constructed and used for classification through Convolutional Neural Network (CNN). As CFMs contain spatial information, they are able to distinguish ASD and control subjects better than other features. Rigorous experimentation has been performed on the EEG datasets collected from Italy and Saudi Arabia according to different criteria. MI feature shows the best result for categorizing ASD and control participants with increased sample size and segmentation.

Purpose: A high-quality primary care clinic should provide clear action points and important care coordination for a child receiving a new diagnosis of autism spectrum disorder (ASD). Unfortunately, a substantial proportion of caregivers report little-to-no post-diagnosis support from their home clinics and primary care providers often report lack of training and resources in providing these supports., Methods: We implemented an intervention package to investigate the impact on the frequency and quality of follow-up care for children with ASD in a busy, high-volume resident continuity clinic. The package consisted of a care coordination scheduling pathway and a standardized clinical template-embedded in the electronic health record (EHR)-that guided providers through best-practice recommendations and patient resources., Results: As a result of these interventions, 74% of patients had ASD-specific follow-up, a more than threefold increase from baseline with a majority of providers using the EHR-embedded template to guide their visit. Providers also indicated a high degree of usability for the system and that it aided them in following best-practice guidelines for ASD care., Conclusion: Through explicit scheduling pathways and a novel EHR template, we saw a significant increase in ASD-specific follow-up visits and implementation of best practices for ASD care, demonstrating a new process for training and engaging primary care providers in clear action steps for post-diagnostic care without having to rely on tertiary referrals., Competing Interests: Declarations. Competing Interests: The authors declared no potential conflicts of interest with respect to research, authorship, and/or publication of this article., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Objective: To determine the accuracy of the Parent's Observation of Social Interactions (POSI) when deployed for universal autism screening within a large healthcare network., Study Design: Retrospective analysis of electronic health record data from children screened for autism spectrum disorder (ASD) using POSI at the 18- and 24- month pediatric well-child care (WCC) visits across Southern California Permanente Medical Group facilities throughout the 2022 calendar year. Data on ASD diagnoses placed in the electronic health record problem list were analyzed 1 year later (until the end of 2023) to calculate sensitivity, specificity, and positive/negative likelihood ratio (LR+ and LR-) values., Results: At the 18-month WCC, 8014 of 30 375 children (26.4%) had elevated POSI scores of ≥3 (positive screen), and the sensitivity and specificity were 77.9% and 76.1%, respectively. At the 24-month WCC, 5988 children of 27 975 (21.4%) had positive POSI screens, and the sensitivity and specificity were 76.5% and 81.4%, respectively. The LR+ was 3.3 at 18 months and 4.2 at 24 months. The LR- was 0.29 at both the 18- and 24-month time points., Conclusions: The POSI screen for ASD had adequate sensitivity and specificity (both >76%) when systematically deployed in a primary care setting at 18- and 24-month WCC visits. Children diagnosed with ASD were 3.3 and 4.2 times more likely to have screened positive at 18 and 24 months, compared with children who were not diagnosed with ASD. Conversely, children not diagnosed with ASD were 3.4 times more likely to have screened negative than children with ASD at 18 and 24 months., Competing Interests: Declaration of Competing Interest The authors declare no conflicts of interest., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Objective: To examine the association between threatened miscarriage, and neurodevelopmental disorders, including autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) in offspring by age 14 years., Methods: We used data from the Millennium Cohort Study, a nationally representative longitudinal study of children born in the UK. Data on threatened miscarriage and potential confounders were maternal-reported and collected at 9 months postpartum. Data on ASD and ADHD were based on maternal-reported doctor diagnoses and collected when children were aged 5, 7, 11 and 14 years. A diagnosis of ASD or ADHD was assumed if parents reported ASD or ADHD at age 5, 7, 11 or 14 years. Crude and adjusted logistic regression examined threatened miscarriage and ASD and ADHD relationship, adjusting for several sociodemographic, maternal and lifestyle factors., Results: A total of 18,294 singleton babies were included at baseline, and 1,104 (6.0%) women experienced a threatened miscarriage during their pregnancy. Adjusted results suggested an association between threatened miscarriage and ASD (OR: 1.55, 95% CI 1.15, 2.08), and ADHD (OR: 1.51, 95% CI 1.09, 2.10) by age 14 years. E-values for threatened miscarriage and ASD were 2.47, while the lower limits of the 95% CI were 1.57. E-values for threatened miscarriage and ADHD were 2.39, while the corresponding lower limits of the 95% CI were 1.40., Conclusion: Threatened miscarriage was associated with an increased likelihood of ASD and ADHD by the age of 14 years, however, residual confounding cannot be ruled out. Placental pathology may be a potential mechanism for the observed associations., Competing Interests: Declaration. Competing Interests: All authors declare that they have no affiliations/involvement with any financial or non-financial interest in the subject matter discussed in this manuscript., (© 2024. The Author(s).)

Autism spectrum disorder, or autism, is a neurodevelopmental disorder of the developing child's brain with a genetic causality. It can be diagnosed at about three years after birth when it begins to present itself via a range of neuropsychiatric symptoms. Nitric oxide is a crucial small molecule of life synthesized within cells of our body systems, including cells of our brain. Peroxynitrite is the product of reaction between superoxide anion and nitric oxide. It normally isomerizes into harmless nitrates or nitrites. However, when excessive superoxide anion is present, the cellular concentration of peroxynitrite can increase to a toxic level. Autism has been suggested to cause oxidative damage to brain cells. Until now, it is impossible to sample tissue from a live brain. Instead, stem cells can be derived (from an autism patient's somatic cells) which can then be differentiated and chemically directed to grow into miniature 3-dimensional tissue masses resembling specific brain regions (e.g., the cortex) called brain organoids. This review discusses utilizing nitric oxide and peroxynitrite as biomarkers and comparing their relative concentrations in stem cells and stem cell derived brain organoids of healthy and autistic individuals to develop a bioanalytical process for early diagnosis of autism., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2025 Elsevier B.V. All rights reserved.)

Purpose: Wellbeing refers to a person's overall happiness and satisfaction with life. Wellbeing for people with Intellectual and Developmental Disabilities (I/DD) and their families is historically significantly lower compared to the general population. It is important in the context of behavioral health treatment to not only measure the individual who is receiving treatment's overall wellbeing, but also the wellbeing of the family. The purpose of this study was to understand the initial psychometric properties of the Catalight Family Wellbeing Scale., Methods: The Catalight Family Wellbeing Scale was developed for families who have a child with I/DD. Caregivers of 3106 families who have a child with a diagnosed I/DD, including autism spectrum disorder, completed the scale as part of their onboarding for behavioral health treatment along with three other questionnaires. The psychometric properties including internal reliability and factor structure were completed as well as initial convergent and divergent validity., Results: Results of the analyses revealed very strong internal reliability and a three-factor structure. Validity analyses revealed a moderate positive relationship with parental self-efficacy and a moderate negative relationship with parental stress. Additionally, the sample population represents an ethnically diverse group with multiple co-occurring diagnosis in addition to I/DD., Conclusions: The initial psychometric properties of the Catalight Family Wellbeing Scale are positive and support the use of the scale for families who have a child with I/DD across a diverse sample., Competing Interests: Declarations. Competing Interests: We have no known conflicts of interest to disclose., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Autism Spectrum Disorder (ASD) is a neurological condition, with recent statistics from the CDC indicating a rising prevalence of ASD diagnoses among infants and children. This trend emphasizes the critical importance of early detection, as timely diagnosis facilitates early intervention and enhances treatment outcomes. Consequently, there is an increasing urgency for research to develop innovative tools capable of accurately and objectively identifying ASD in its earliest stages. This paper offers a short overview of recent advancements in non-invasive technology for early ASD diagnosis, focusing on an imaging modality, structural MRI technique, which has shown promising results in early ASD diagnosis. This brief review aims to address several key questions: (i) Which imaging radiomics are associated with ASD? (ii) Is the parcellation step of the brain cortex necessary to improve the diagnostic accuracy of ASD? (iii) What databases are available to researchers interested in developing non-invasive technology for ASD? (iv) How can artificial intelligence tools contribute to improving the diagnostic accuracy of ASD? Finally, our review will highlight future trends in ASD diagnostic efforts., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2025 Elsevier B.V. All rights reserved.)

The aim of this study was to examine the reliability and validity of the Turkish version of the AFEQ for Turkish parents of children with ASD. The Turkish-translated version of the AFEQ was administered to 241 parents of children aged 2-12 years with ASD to examine the construct validity and internal consistencies. Parents completed the Autism Behavior Checklist (ABC), and Quality of Life in Autism Questionnaire Parent version, along with the AFEQ. The mean age of the children of 241 individuals in the study group was 7.63 ± 3.02 and 88.4% (n = 213) were male. Cronbach's alpha coefficient was 0.921 of the total variance. Cronbach alpha coefficients are 0.813 for the "Experience of being a parent" subscale, 0.768 for the "Family Life" subscale, 0.810 for the "Child Development, Understanding and Social Relationships" subscale, and 0.804 for the "Child Symptoms (Feelings and Behaviour)" subscale. In conclusion, the translated and culturally adapted AFEQ shows good reliability and validity to measure the priorities of autistic children and their families in Turkey. It can also be useful in monitoring the effectiveness of intervention programs and changes in the child., Competing Interests: Declarations. Conflict of interest: The authors have no competing interests to declare that are relevant to the content of this article. Ethical Approval: Approval for this study was obtained from the ethics committee of University Eskisehir Osmangazi University of Medicine School and Eskisehir Provincial Directorate of National Education (approval no: 2020/507). All procedures adhered to the principles of the Declaration of Helsinki., (© 2024. The Author(s).)

Objective: Social communication difficulties are a characteristic of autism spectrum disorder (ASD), a neurodevelopmental condition. The earlier method of diagnosing autism largely relied on error-prone behavioral observation of symptoms. More intelligence approaches are in progress to diagnose the disorder, which still demands improvement in prediction accuracy. Furthermore, computer-aided design systems based on machine learning algorithms are extremely time-consuming and difficult to design. This study used deep learning techniques to develop a novel autism detection model in order to overcome these problems., Methods: Preprocessing, Features extraction, Improved Feature level Fusion, and Detection are the phases of the suggested autism detection methodology. First, both input modalities will be preprocessed so they are ready for the next stages to be processed. In this case, the facial picture is preprocessed utilizing the Gabor filtering technique, while the input EEG data is preprocessed through Wiener filtering. Subsequently, features are extracted from the modalities, from the EEG signal data, features like Common Spatial Pattern (CSP), Improved Singular Spectrum Entropy, and correlation dimension, are extracted. From the face image, features like the Improved Active Appearance model, Gray-Level Co-occurrence matrix (GLCM) features and Proposed Shape Local Binary Texture (SLBT), as well are retrieved. Following extraction, enhanced feature-level fusion is performed to fuse the features. Ultimately, the combined features are fed into the hybrid model to complete the diagnosis. Models such as Convolutional Neural Networks (CNN) and Bidirectional Gated Recurrent Units (Bi-GRU) are part of the hybrid model., Results: The suggested MADDHM model achieved an accuracy of about 91.03 % regarding EEG and 91.67 % regarding face analysis meanwhile, SVM=87.49 %, DNN=88.59 %, Bi-GRU=90.02 %, LSTM=87.49 % and CNN=82.02 %., Conclusion: As a result, the suggested methodology provides encouraging outcomes and opens up possibilities for early autism detection. The development of such models is not only a technical achievement but also a step forward in providing timely interventions for individuals with ASD., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

Aim: Autism spectrum disorder (ASD) is a common neurodevelopmental disorder. This study aims to investigate the impact of an ASD diagnosis on children and their carers from a regional/rural Australian perspective., Methods: A three-part survey development study included: (i) Semi-structured individual ASD carer interviews to identify common themes; (ii) survey development and testing; and (iii) online survey circulation to wider group of carers, for data collection and analysis., Results: Transcripts from eight carer interviews guided the development of 65 survey questions. The survey was circulated to 316 carers of children diagnosed with ASD. Of the 101 respondents, 95% were female, 86% regional and 12% were rural inhabitants. The average child's age at diagnosis was 6.64 years. Most carers (93%) reported that diagnosis of ASD met their goal, for some an improved understanding of their child's behaviour (39%) and allowing access to therapy (16%), government disability funding (National Disability Insurance Scheme) (19%) and learning support (9%). Some (44%) reported no downsides to an ASD diagnosis; however, 38% reported fears of discrimination, particularly with future relationships (5%) and employment (14%). Barriers included waiting times (16%), costs of appointments (9.9%) and difficulty navigating through the health system (5.9%). Only five participants reported having no costs associated with appointments., Conclusions: Carers had positive attitudes and experiences regarding their child's ASD diagnosis. The benefits outweighed the perceived harms. Barriers to accessing services included waiting times, out-of-pocket expenses and travel distance., (© 2024 Paediatrics and Child Health Division (The Royal Australasian College of Physicians).)

Objectives: The primary objective of this study was to determine the effects of permanent, mediated parental presence during all autism spectrum disorder diagnostic evaluations on parental adjustment (perceived parental stress and sense of parental competence) compared with procedures that traditionally only involve parents in pivotal periods of the diagnosis. The level of satisfaction with the diagnostic procedure and parents' needs were also evaluated to complete this first objective. The secondary objective was to assess the effects of psychosocial, individual, and contextual variables on perceived parental stress and sense of parental competence., Methods: The total sample of 49 parents was divided (using simple randomization) into two subgroups, each for a different procedure. Participants were met with once before the first consultation and once after. They completed self-reported questionnaires on parental stress, sense of parental competence, satisfaction with the procedure, social support, locus of control, and appraisal of life events. Statistical analysis was conducted using SPAD and SPSS software., Results: There was no difference between the two groups in the variables assessed. Satisfaction with the diagnostic procedure was high in both groups, but parents highlighted that they had important needs following the diagnosis. The child's level of autonomy, the presence of disruptive behaviors, and satisfaction with social support were found to be important for determining parental adjustment., Conclusions: Several hypotheses may explain the lack of differences between the two groups, including that parents may not yet have been in a position to benefit from the procedure aimed at integrating them. Our suggestion is that professional interventions should focus on improving the child's autonomy and helping the parent to develop a satisfactory support network. Finally, parents' needs for the post-diagnosis phase should be given greater consideration, particularly in future research., (Copyright © 2024 L'Encéphale, Paris. Published by Elsevier Masson SAS. All rights reserved.)

Social attention is a key aspect of neurodevelopment and is significantly altered in neurodevelopmental genetic syndromes and many individuals with idiopathic autism spectrum disorder (ASD). The primary aim of the present study was to examine the psychometric properties of webcam-collected social attention measurements, including four new specific aspects of social attention, in three genetic syndromes (PTEN Hamartoma Tumor Syndrome-PHTS; Malan Syndrome-NFIX; and SYNGAP1-related disorder-SYNGAP1), a mixed group of other neurodevelopmental genetic syndromes (Other NDGS), and individuals with a range of idiopathic neurodevelopmental disorder (NDD). The secondary aim was to evaluate the construct validity of these social attention measurements, including evaluating known-groups validity across study groups and concurrent validity for separating ASD and non-ASD cases. Participants (N = 467, age 3-45; PHTS n = 102, NFIX n = 23, SYNGAP1 n = 42, other NDGS n = 63, idiopathic NDD n = 53, neurotypical siblings n = 71, and unrelated neurotypical controls n = 113) completed a 4-min online-administered social attention paradigm that includes a variety of distinct stimuli at three timepoints (baseline, 1-month, and 4-month follow-up). Social attention measures had good scale and test-retest reliability, with the exception of measures of non-social preference and face-specific processing. Unique patterns of social attention emerged across study groups, with near neurotypical levels in PHTS and weaker social attention in NFIX and SYNGAP1 relative to controls. Global social attention had good accuracy in detecting ASD within NDGS participants. Remote monitoring social attention, including distinct aspects of social attention, may be useful for characterizing phenotypic profiles and tracking the natural history of distinct NDGS and idiopathic NDD as well as identifying ASD within NDGS. Given their reproducibility and stability, global social attention and several distinct social attention measures may be useful outcomes for future clinical trials., (© 2024 The Author(s). Autism Research published by International Society for Autism Research and Wiley Periodicals LLC.)

The COVID-19 pandemic and the subsequent social distancing policies forced healthcare teams to drastically alter the way they deliver services. This was particularly challenging for clinicians involved in diagnosing autism spectrum disorder (ASD), as assessment tools and methods required face-to-face social interactions between clinicians and children. To address this, the Brief Observation of Symptoms of Autism (BOSA) was developed to ensure that people suspected of ASD can receive diagnostic assessments during the pandemic. This project aimed to explore clinicians' opinions on the BOSA, particularly regarding the usefulness of the assessment for clinicians to clarify diagnostic outcomes of ASD assessments. Both quantitative and qualitative data was gathered within an NHS community paediatric team. This included a questionnaire for clinicians to complete, and data from the BOSA assessments done in the service. Thematic analysis and descriptive statistics revealed that many clinicians felt that the BOSA can be beneficial in certain cases, such as selective mutism, and found the BOSA particularly helpful for observing parent-child interactions. These findings highlighted important information that the Autism Diagnostic Observation Schedule Second Edition (ADOS-2) does not give opportunities to observe. Clinicians reported that at times, the BOSA materials, brevity and parental administration created barriers to gathering information for diagnostic decisions. As may be expected, clinicians showed a clear preference for the more familiar and validated ADOS-2. However, the study highlights perceived limitations of the ADOS-2 and strengths of the BOSA, with recommendations made for future practice and research., Competing Interests: Declarations. Conflict of Interest: All authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest or non-financial interest in the subject matter or materials discussed in this manuscript. Ethical Approval: Ethical approval was received from the Faculty of Medicine and Health Sciences Research Ethics Committee at the University of East Anglia (ethics reference code: 2021/22-020). Consent to complete the project within the local NHS service was granted by the trust’s Clinical Audit & Effectiveness Team. Informed Consent: Informed consent was obtained from all individual participants included in the study and for data to be submitted for publication., (© 2024. The Author(s).)

There are no assessment and screening tools for Autism Spectrum Disorders (ASD) validated for the Portuguese population. The Social Communication Questionnaire (SCQ) is an useful screening tool of ASD diagnosis. The main objectives of our study were to produce a Portuguese version of the SCQ (SCQ-PF), study its internal consistency, sensitivity and specificity in order to evaluate its validity as a screening instrument for ASD. We also wanted to study the impact of intellectual disability and verbal impairment and other mental disorders on SCQ-PF psychometric properties. The study included 211 children and adolescents, aged 4-17, divided in three groups: ASD Group (n = 96), Other Mental Disorders Group (OMD) (n = 63) and No Mental Disorders (NMD) Group (n = 52). Parents or other primary caregiver provided information on the SCQ items. The SCQ-PF score was significantly higher in the ASD group than in the other groups (p < 0.001). As to internal consistency, Cronbach's alpha was 87%. ASD subjects were distinguished from subjects without ASD (OMD and NMD Groups) and the area under the curve (AUC) was 0.897 (95% Confidence Interval: 0.852-0.943), for a cutoff of 14, which yielded the highest AUC, with values of sensitivity and specificity 0.76 and 0.93, respectively. These findings show that SCQ- PF with a cutoff of 14 is an acceptable and useful screening tool for ASD in the Portuguese population., Competing Interests: Declarations. Conflict of interest: The authors declare that they have no conflict of interest. No funding was received for conducting this study. Ethical Approval: All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. This article does not contain any studies with animals performed by any of the authors. Informed Consent: Informed consent was obtained from all individual participants included in the study., (© 2023. The Author(s).)

Background: Black families of children with autism spectrum disorder have less access to high quality, culturally responsive care for their children., Method: We assessed satisfaction and service utilization among fifty (29%) Black caregivers and 124 (71%) White caregivers of children with autism spectrum disorder. We also examined whether race moderated the association between satisfaction and service utilization., Results: We did not identify racial differences in satisfaction or service utilization. Race moderated the association between satisfaction and total service use, F(170) = 5.29, p =.02, therapy service use, F(163) = 3.59, p =.046, and community service use, F(169) = 4.76, p =.046. For Black families, there was a positive association between satisfaction and service use. There was no association between satisfaction and service use among White families., Discussion: Satisfaction may be particularly important among Black families, who have been mistreated by the healthcare system and frequently face discrimination. Our results suggest the importance of culturally responsive care for Black families., Competing Interests: Declarations. Conflict of Interest: All authors declare no conflicts of interest., (© 2024. The Author(s).)

Individuals with autism spectrum disorder (ASD) display heterogeneity in adaptive functioning, underscoring the need to identify predictors to inform clinical and scientific interventions. We investigated the longitudinal associations between an autism diagnosis, co-occurring psychopathology symptoms, executive functions (EF) and subsequent adaptive functioning in individuals with and without ASD (IQ > 70). Sixty-six individuals (26 with ASD, 40 without ASD) were assessed at baseline (mean age = 11.8 years, SD = 2.1) and at 10-year follow-up (mean age 21.4, SD = 2.3). The diagnostic evaluation comprised a comprehensive assessment of autism symptoms and emotional and cognitive functioning. Co-occurring psychopathology symptoms were assessed with two measures: self-reported depressive symptoms with the Short Mood and Feelings Questionnaire and parent-reported total problems with the Child Behavior Checklist 6-18. Participants completed neuropsychological tests to evaluate EF. We investigated adaptive functioning by using the Weiss Functional Impairment Rating Scale (WFIRS) which is a self-report measure of impairment in the following domains: family, work, school, life skills, self-concept, social and risk-taking. Among the emerging adults previously diagnosed with ASD, 46% reported living independently, 75% had at least one friend, and 71% were employed or in education. Individuals with ASD reported significantly lower adaptive functioning compared to individuals without ASD (WFIRS Total, Hedges' g = 0.92). Greater EF difficulties in childhood/adolescence predicted lower adaptive functioning in emerging adulthood, surpassing the influence of autism diagnosis and co-occurring symptoms. The findings highlight the influential role of EF, implying that interventions targeting EF difficulties could improve long-term outcomes for individuals with ASD., Competing Interests: Compliance with Ethical Standards. Funding: This work was supported by grants from Innlandet Hospital Trust (grant numbers: 150663, 150610, 150624, and 150648), South-Eastern Norway Regional Health Authority (grant number 2022004), and the Norwegian Centre of Expertise for Neurodevelopmental Disorders and Hypersomnias, Department of Rare Disorders and Disabilities, Oslo University Hospital (grant number: 150616). Open access funding provided by University of Oslo (incl Oslo University Hospital) Conflict of Interest: We have no conflict of interest. Ethical Approval: This study was prospectively reviewed and approved by the Regional Committee for Medical Research Ethics in Eastern Norway (T1-T2: REK 6-2009-24; T3: 2018/1611) and the Privacy Ombudsman for Research at Innlandet Hospital Trust. The study was conducted in accordance with the Helsinki Declaration of the World Medical Association Assembly., (© 2024. The Author(s).)

Children and adolescents with neurodevelopmental disorders demonstrate extensive cognitive heterogeneity that is not adequately captured by traditional diagnostic systems, emphasizing the need for alternative assessment and classification techniques. Using a transdiagnostic approach, a retrospective cohort study of cognitive functioning was conducted using a large heterogenous sample ( n  = 1529) of children and adolescents 7 to 18 years of age with neurodevelopmental disorders. Measures of short-term memory, verbal ability, and reasoning were administered to participants with attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), comorbid ADHD/ASD, and participants without neurodevelopmental disorders (non-NDD) using a 12-task, web-based neurocognitive testing battery. Unsupervised machine learning techniques were used to create a self-organizing map, an artificial neural network, in conjunction with k-means clustering to identify data-driven subgroups. The study aims were to: 1) identify cognitive profiles in the sample using a data-driven approach, and 2) determine their correspondence with traditional diagnostic statuses. Six clusters representing different cognitive profiles were identified, including participants with varying forms of cognitive impairment. Diagnostic status did not correspond with cluster-membership, providing evidence for the application of transdiagnostic approaches to understanding cognitive heterogeneity in children and adolescents with neurodevelopmental disorders. Additionally, the findings suggest that many typically developing participants may have undiagnosed learning difficulties, emphasizing the need for accessible cognitive assessment tools in school-based settings.

Objective: Pain in children and adolescents with autism spectrum disorders remains underdiagnosed due to their inherent communication difficulties. The goal of this review is to identify the most suitable methods for assessing pain in this population and for evaluating the specific perceptions of, or behavioural reactions to, pain whilst considering disorder severity and specifiers (with or without accompanying intellectual impairment, with or without accompanying language impairment)., Method: A systematic review and analysis of the international literature was conducted., Results: Fourteen studies were selected. No difference was found in pain-related behaviours based on the age or gender of children or adolescents with autism. Three studies showed pain-related behaviours in autism spectrum disorders to be similar to control groups. Other studies showed specific behavioural responses in autism spectrum disorders with a longer physiological and behavioural recovery time associated with an episode of acute pain in this population. Similarly, the three studies that focused on sensory perceptions of pain all showed differences in the autism spectrum disorders population compared to control groups. In hospital or daily life contexts, studies essentially showed idiosyncratic expressions, hypervigilance, motor agitation, negative emotional reactions, or vocalizations. Regarding the association of autism severity with hyposensitivity to pain, the results remain unclear even when language disorders or intellectual disabilities are also present (in conjunction with autism). The Non-Communicative Children Pain Checklist and its translation into French and Italian showed good internal validity and was used by almost half of the studies in hetero-assessment, mostly by parents. Studies recommend the inclusion of parents in the assessment in order to optimise the evaluation process. Similarly, analysis of parent/child/caregiver interviews from the studies highlights the importance of personalizing pain assessment of children and adolescents, taking into account subject-specific characteristics, pathology, and context., Conclusion: An integrative and personalized approach to pain assessment appears to be the most appropriate for enhancing the understanding and detection of pain in individuals with autism spectrum disorders. This approach aligns well with a care setting where a nominated professional with a good expertise in autism is responsible for pain assessment. Given the complexity of identifying pain in individuals with autism, further qualitative studies, in conjunction with new pain exploration technologies, are considered necessary as well as a more extensive categorization of the population studies., (Copyright © 2024 L'Encéphale, Paris. Published by Elsevier Masson SAS. All rights reserved.)

Background: Early screening for autism spectrum disorder (ASD) is crucial, yet current assessment tools in Chinese primary child care are limited in efficacy., Objective: This study aims to employ machine learning algorithms to identify key indicators from the 20-item Modified Checklist for Autism in Toddlers, revised (M-CHAT-R) combining with ASD-related sociodemographic and environmental factors, to distinguish ASD from typically developing children., Methods: Data from our prior validation study of the Chinese M-CHAT-R (August 2016-March 2017, n = 6,049 toddlers) were reviewed. We extracted the 20-item M-CHAT-R data and integrated 17 sociodemographic and environmental risk factors associated with ASD development to strengthen M-CHAT-R's machine learning screening. Five feature selection methods were used to extract subsets from the original set. Six machine learning algorithms were applied to identify the optimal subset distinguishing clinically diagnosed ASD toddlers from typically developing toddlers., Findings: Nine features were grouped into three subsets: subset 1 contained unanimously recommended items (A1 [Follows point], A3 [Pretend play], A9 [Brings objects to show], A10 [Response to name] and A16 [Gazing following]). Subset 2 added two items (A17 [Gaining parent's attention] and A18 [Understands what is said]), and subset 3 included two more items (A8 [Interest in other children] and child's age). The top-performing algorithm resulted in a seven-item classifier of subset 2 with 92.5 % sensitivity, 90.1 % specificity, and 10.0 % positive predictive value., Conclusions: Machine learning classifiers effectively differentiate ASD toddlers from typically developing toddlers using a reduced M-CHAT-R item set., Clinical Implications: This highlights the clinical significance of machine learning-optimized models for ASD screening in primary health care centers and broader applications., Competing Interests: Declaration of competing interest The authors have indicated they have no potential conflicts of interest to disclose and have no financial relationships relevant to this article to disclose., (Copyright © 2025 The Author(s). Published by Elsevier B.V. All rights reserved.)

Background: Autism commonly co-occurs with attention-deficit/hyperactivity disorder (ADHD), but less is known regarding how ADHD symptoms impact the early presentation of autism. This study examined early behavioral characteristics of a community sample of toddlers later identified with autism diagnosis, ADHD symptoms, combined autism and ADHD symptoms, or neither condition., Methods: Participants were 506 toddlers who were part of a longitudinal study of children's behavioral development. Parents completed questionnaires about their children's behavior at two time points. Four groups were identified based on study measures or medical record: autism diagnosis (n = 45), elevated ADHD symptoms (n = 70), autism and ADHD symptoms (n = 30), or neurotypical development (n = 361). Relationships between early parent report of autism- and ADHD-related behaviors, social-emotional and behavioral functioning, and caregiver experience and subsequent group designation were evaluated with adjusted linear regression models controlling for sex., Results: Significant group differences were found in measures of autism-related behaviors, ADHD-related behaviors, externalizing and internalizing behaviors, and parent support needs (p < .0001). Pairwise comparisons indicated toddlers later identified with combined autism diagnosis and ADHD symptoms had higher levels of autism-related behaviors, externalizing and internalizing behaviors, and autism-related parent support needs compared to the other groups. Toddlers with subsequent elevated ADHD symptoms or combined autism diagnosis and ADHD symptoms exhibited similar levels of ADHD-related behaviors, while both groups displayed more ADHD-related behaviors than toddlers subsequently identified with autism or those with neither condition., Conclusions: In this community sample, toddlers for whom combined autism diagnosis and ADHD symptoms were subsequently identified showed a distinct presentation characterized by higher early autism-related behaviors, broader behavioral concerns, and higher parent support needs. Presence of ADHD symptoms (alone or in combination with autism) was associated with higher parent-reported ADHD-related behaviors during toddlerhood. Results indicate that ADHD-related behaviors are manifest by toddlerhood, supporting screening for both autism and ADHD during early childhood., (© 2024 Association for Child and Adolescent Mental Health.)

Background: Autism spectrum disorder (ASD) appears to be a common neurological developmental deficit disorder in pediatric patients, resulting in a tremendous burden on society., Purpose: The article aimed to explore early diagnostic markers for ASD., Methods: Levels of long non-coding RNA (lncRNA) H19 and microRNA-484 (miR-484) were detected using fluorescence quantitative polymerase chain reaction (PCR). The Spearman method was applied for the correlation analysis with ASD severity. To evaluate the role of H19 and miR-484 role in ASD diagnosis, the receiver operator characteristic (ROC) curve was plotted. Luciferase reporter assay was used to confirm the targeting relationship between H19 and miR-484. The functions and pathways related to miR-484 target genes were annotated by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis., Results: Elevated H19 levels were detected in ASD patients, which was positively correlated with disease severity. MiR-484 showed a decreasing trend in ASD patients, while it was negatively related to disease severity. Both H19 and miR-484 can distinguish ASD cases from controls with an AUC of 0.878 and 0.868, respectively. Luciferase reporter assay determined the target relationship between H19 and miR-484., and their combination showed the highest diagnostic value for ASD (AUC = 0.906). GO and KEGG analysis demonstrated the targeted genes of miR-484 were related to the development of ASD, and EIF4G2 and SMARCA2 were the main core genes., Conclusion: H19 and miR-484 were dysregulated in ASD patients and were both associated with disease severity. The combined H19 and miR-484 represented a high diagnostic value for ASD., (© 2025 International Society for Developmental Neuroscience.)

Introduction: The association between increasing diagnosis rates of autism-related disorders (ASD-R) in Swedish regions and diagnosis rates of major depressive disorders (MDD) in adolescents remains unexplored., Methods: Following STROBE guidelines, this pre-registered (https://osf.io/duvq7) observational study, utilizing registry data from 2008 to 2022 across the 21 Swedish regions, employed a generalized linear mixed model (GLMM) to analyze the association between ASD-R (ICD-10: F84) and MDD diagnosis rates (ICD-10: F32) in 15-19 year olds, with registered primary diagnoses considered. The GLMM included psychiatric care affiliation rates (PCAR) as fixed effects and variations across years and regions as random intercepts. The model incorporated bipolar disorder (BD) rates and the male-to-female ratio of ASD-R diagnoses when justified. Separate models were created for combined sexes, males, and females., Results: A significant inverse relationship was observed between ASD-R and MDD diagnosis rates across all sex groups. In the combined-sex model, the mean ratio was 0.40 (P = 0.003), while the sex-specific models showed ratios of 0.28 for males (P < 0.001) and 0.37 for females (P = 0.017). All ratios were significantly below 1, indicating a negative association between ASD-R and MDD diagnosis rates., Conclusions: The study's observational nature limits causal inferences, but findings reveal that higher primary diagnosis rates of ASD-R correlate with lower primary diagnosis rates of MDD in adolescents of both sexes, although more pronounced in males. These results highlight the importance of further research on the relationship between ASD-R and MDD diagnosis rates, emphasizing the need for prospective, longitudinal, and individualized register data that include both primary and co-diagnoses., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Autism Spectrum Disorder (ASD) is a prevalent neurodevelopmental condition for which no prenatal or early life screening tests exist. Early life recognition of ASD is key to accessing behavioral intervention when brain plasticity is at its peak. The purpose of our study was to systematically review the literature researching parental perspectives around early life screening for autism and specifically genetic testing. A total of 30 studies were included and coded against the following variables: parental characteristics, child characteristics, research design, data collection and data analysis methods, type of early screening, and parental perspectives towards early life screening and genetic testing. The outcomes of the review showed that caregivers need more knowledge about ASD genetic testing, they are in general in favor of early life screening, and they prefer to access ASD genetic testing and early behavioral intervention as early as possible. As emerging genetic tests are likely to increase diagnostic accuracy for ASD in the near future, it is of paramount importance for research and practice to embrace parental needs and preferences. Healthcare providers can be pivotal in empowering parents to make informed decisions through clear, compassionate communication and counseling. Future research should seek to fill in an essential gap in the literature, which is to capture parental views from a diverse population., Competing Interests: Declarations. Conflict of interest: The authors have no financial or non-financial interests to disclose. Ethical Approval: This article does not contain any studies with human participants or animals performed by any of the authors., (© 2024. The Author(s).)

Background: We validated the German version of the Glasgow Sensory Questionnaire (GSQ), a self-report questionnaire for adults assessing the processing of stimuli regarding hypo- and hypersensitivity in seven sensory modalities. Since the GSQ is intended for the use in autistic adults, we aimed to complement our previous study on students with high and low Autism Spectrum Quotient (AQ; Zeisel et al., BMC Psychiatry 23:426, 2023), by surveying groups of autistic and non-autistic adults, to present the sensory processing profiles of the two groups, to identify the factor structure of the questionnaire in a group of autistic individuals and to identify the diagnostic value of a cut-off score for heightened sensory sensitivity in German autistic adults., Methods: A sample of autistic and non-autistic adults (each n = 86) completed the same German version of the GSQ as used in Zeisel et al. (BMC Psychiatry 23:426, 2023), the AQ and the Symptom Checklist-90-Revised. Factor analyses were applied., Results: The German GSQ showed good to excellent reliability. While the factor structure could not be confirmed, main findings of other validation studies were replicated: AQ and GSQ scores were moderately to strongly associated, with higher AQ and GSQ scores for autistic than for non-autistic individuals. Autistic individuals also showed more consistency in their sensitivity across sensory modalities. A third of the autistic participants had heightened sensory sensitivity, when a cut-off was set at the 95th percentile of the non-autism group., Conclusions: Overall, this German version of the GSQ can be considered a validated self-report questionnaire assessing sensory sensitivity particularly in autistic individuals. It can be used to assess sensory sensitivity in the diagnostic process of autism spectrum disorder and to assess an individual's sensory needs and strengths for best possible support. Further studies are required, especially to assess the internal structure of the GSQ., Competing Interests: Declarations. Ethics approval and consent to participate: The study was approved by the ethics committee of the TUD Dresden Technische Universität (ethical approval code: EK 356092018) and carried out in accordance with these regulations and the declaration of Helsinki. All participants and when applicable in the case of autistic participants their guardians gave written informed consent. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests., (© 2025. The Author(s).)

Current research often overlooks anxiety symptoms in preschoolers with Autism Spectrum Disorder (ASD), focusing on older children. This study examines anxiety symptomatology primarily in young children with ASD by analyzing data from 82 Spanish children aged 3- to 6 years. Parents completed the Anxiety Scale for Children with ASD and the Social Communication Questionnaire. Results indicate that 30.48% of the children exhibit significant anxiety symptoms, "with anxious uncertainty" being the most prevalent. Factor analysis reveals three principal components of the Anxiety Scale, supporting its reliability. Regression analysis highlights stereotypical behaviors as significant predictors of anxiety levels. These findings underscore the importance of early assessment and adaptation of assessment tools for preschoolers with ASD. Stereotypical behaviors are identified as key predictors of anxiety in this population., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2025 Durán-Bouza et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: Intellectual developmental disorder with autism and speech delay (IDDAS) is a rare and complex neurological disorder characterized by the presence of both intellectual and speech impairment and features of autism spectrum disorder (ASD). The prevalence of IDDAS is unknown but genetically, it is caused by heterozygous variants in the TBR1 gene., Methods: A 7-year-old female with autistic features and delayed speech development was presented with unaffected parents. Trio-joint analysis was conducted on whole-genome sequencing (WGS) data from the proband and unaffected parents. A phenotype-driven analysis was conducted to investigate variants related to the patient's clinical presentation. A zygosity-focused analysis was performed to investigate de novo and compound heterozygote variants related to the etiology., Results: The joint-genome analysis identified a novel NM&#95;006593.4( TBR1 ):c.1303C>T p.Gln435* nonsense variant in the proband. The de novo analysis confirmed the absence of the variant in the parents. No additional causative variants were identified in genes associated with the proband's phenotype., Conclusions: This is the first report of the NM&#95;006593.4( TBR1 ):c.1303C>T variant in a patient with IDDAS. This study presents the clinical features of the patient and highlights details of trio-WGS analysis in the molecular diagnosis of this complex disease. Sharing these details is important, as they contribute to the understanding of the spectrum of this rare syndrome.

The purpose of this study was to investigate the expression of miR-499a-5p in children with autism spectrum disorders (ASD) and its value in early diagnosis of ASD. This is a retrospective case-control study that included 40 children with ASD as a case group and 43 healthy children as a control group. Magnetic resonance imaging (MRI) was performed on all subjects, and the children were scored with childhood autism rating scale (CARS) and autism behavior checklist (ABC). The expression of miR-499a-5p in serum was detected by RT-qPCR, and the diagnostic value of miR-499a-5p in ASD was evaluated by ROC curve. Pearson correlation coefficient was used to evaluate the correlation between miR-499a-5p levels and scores. Compared with healthy children, the expression level of serum miR-499a-5p was significantly reduced in children with ASD. ROC curve showed that miR-499a-5p is of high diagnostic value for ASD. The results of MRI suggested that the volume of the amygdala in ASD children was significantly larger than that in healthy children, while the volume of the caudate nucleus was significantly reduced. Correlation results showed that the scores of CARS and ABC in the ASD group were significantly negatively correlated with the levels of miR-499a-5p. In the ASD group, the volume of the amygdala was negatively correlated with the level of miR-499a-5p, while the volume of the caudate nucleus was positively correlated with the level of miR-499a-5p. The decreased expression of miR-499a-5p in the serum of children with ASD was significantly related to the changes in brain volume of children with ASD, and the miRNA showed good diagnostic accuracy in children with ASD., Competing Interests: Declarations. Ethics Approval and Consent to Participate: The study protocol was approved by The Ethics Committee of Xingtai People’s Hospital and followed the principles outlined in the Declaration of Helsinki. In addition, informed consent has been obtained from the participants involved. Consent for Publication: Not applicable. Conflict of Interest: The authors declare no competing interests., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Background: Pragmatic language refers to using spoken language to convey messages effectively across diverse social communication contexts. However, minimal longitudinal research has focused on defining early predictors of pragmatic development in children with autism spectrum disorder (ASD)., Methods: In the present study, 71 children with ASD and 38 age- and gender- matched 24- to 30-month-old typically developing (TD) children were enrolled. Social-communication, language, and parent‒child interaction measures were collected for the ASD group at baseline. Three years later, all subjects were assessed for pragmatic ability via the Chinese version of the Language Use Inventory (LUI-Mandarin). First, the differences in pragmatic performance between the ASD and TD groups at follow-up were analyzed. Second, pragmatic performance was correlated with autism symptomatology at follow-up, as well as the structural language difficulties and joint engagement (JE) levels at baseline in the ASD group. Furthermore, hierarchical multiple regression analyses and machine learning techniques were performed to explore the effects of early potential predictors of pragmatic development in the ASD group., Results: First, our results revealed that performance was significantly lower in the ASD than in the TD group with respect to the LUI-Mandarin total scores and subscale scores (except for subscale C). Second, correlation analysis revealed that more severe symptoms of ASD at follow-up were associated with lower LUI-Mandarin total scores and better language performance on the Gesell Developmental Schedules (GDS). Additionally, increased proportions of supported JE (SJE) states were associated with higher LUI-Mandarin total scores. In contrast, increased proportions of unengaged (UE) states were associated with lower LUI-Mandarin total scores in the ASD group. Third, hierarchical multiple regression analyses and machine learning techniques indicated that the proportions of SJE during parent‒child interactions, as well as the degree of social symptoms and structural language impairments, were significant contributors to pragmatic development for the ASD group in the prediction models., Conclusion: In summary, our findings suggest that pragmatic language difficulties are present in children with ASD as early as preschool age. Additionally, given the close correlation between the LUI-Mandarin score and symptom severity on the ADOS/ADI-R, the LUI-Mandarin might be a good way to triage children who need to wait a long time for a more extensive evaluation. Furthermore, this study provides new insights into potential targets for pragmatic interventions, and interventions can be designed to promote SJE between caregivers and children in future work., Competing Interests: Declarations. Ethics approval and consent to participate: This study was approved by the Nanjing Brain Hospital affiliated with the Nanjing Medical University Ethics Committee, participants were consented by an informed consent process that was reviewed by the Ethics Committee of Nanjing Medical University and certify that the study was performed in accordance with the ethical standards as laid down in the 1964 Declaration of Helsinki, and informed consent was obtained from the parents or legal guardians of the participants. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Background and Aims: Autism spectrum disorder (ASD) is a common neurodevelopmental disorder in children. Early intervention is effective. Investigation of novel blood biomarkers of ASD facilitates early detection and intervention., Materials and Methods: Sequential window acquisition of all theoretical spectra-mass spectrometry (SWATH-MS)-based proteomics technology and 30 DSM-V defined ASD cases versus age- and sex-matched controls were initially evaluated, and candidate biomarkers were screened using machine learning methods. Candidate biomarkers were validated by targeted proteomics multiple reaction monitoring (MRM) analysis using an independent group of 30 ASD cases vs. controls., Results: Fifty-one differentially expressed proteins (DEPs) were identified by SWATH analysis. They were associated with the immune response, complements and coagulation cascade pathways, and apolipoprotein-related metabolic pathways. Machine learning analysis screened 10 proteins as biomarker combinations (TFRC, PPBP, APCS, ALDH1A1, CD5L, SPARC, FGG, SHBG, S100A9, and PF4V1). In the MRM analysis, four proteins (PPBP, APCS, FGG, and PF4V1) were significantly different between the groups, and their combination as a screening indicator showed high potential (AUC = 0.8087, 95 % confidence interval 0.6904-0.9252, p < 0.0001)., Conclusions: Our study provides data that suggests that a few plasma proteins have potential use in screening for ASD., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Purpose: The purposes of this article were (a) to compare the developmental skills of toddlers whose scores on the First Years Inventory-Lite (FYI-Lite), an early screening tool, indicated an elevated likelihood of a later diagnosis of autism (ELA) to the developmental skills of toddlers at a lower likelihood of a later diagnosis of autism (LLA) and (b) to examine how autism characteristics are correlated with communication measures in toddlers at an ELA., Method: We assessed the language, social communication (SC) skills, and characteristics of autism demonstrated by 45 toddlers at an ELA and 37 toddlers at an LLA between the ages of 11 and 18 months and compared group scores on these measures. We also examined the correlations between the characteristics of autism and language measures within the ELA group., Results: Toddlers at an ELA demonstrated lower scores on measures of global expressive and receptive language, receptive vocabulary, gestures, and response to joint attention bids as well as SC characteristics of autism when compared to those demonstrated by toddlers at an LLA. There were no significant differences between groups on expressive vocabulary, language profiles (i.e., the relationship between receptive and expressive scores), or restrictive and repetitive behaviors. Within the ELA group, the SC characteristics of autism were significantly associated with their global receptive and expressive language skills., Conclusions: On the basis of the FYI-Lite screening tool, toddlers at an ELA are demonstrating delays in language and SC skills when compared to toddlers identified with an LLA. For toddlers at an ELA, the SC characteristics of autism are significantly associated with early language skills., Supplemental Material: https://doi.org/10.23641/asha.27969444.

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder diagnosed by clinicians and experts through questionnaires, observations, and interviews. Current diagnostic practices focus on social and communication impairments, which often emerge later in life. This delay in detection results in missed opportunities for early intervention. Gait, a motor behavior, has been previously shown to be aberrant in children with ASD and may be a biomarker for early detection and diagnosis of ASD. The current study assessed gait in children with ASD using a single RGB camera-based pose estimation method by MediaPipe (MP). Data from 32 children with ASD and 29 typically developing (TD) children were collected. The ASD group exhibited significantly reduced step length and right elbow° and increased right shoulder° relative to TD children. Four machine learning (ML) algorithms were employed to classify the ASD and TD children based on the statistically significant gait parameters. The binomial logistic regression (Logit) performed the best, with an accuracy of 0.82, in classifying the ASD and TD children. The present study demonstrates the use of gait analysis and ML techniques for the early detection of ASD., Competing Interests: Declarations. Competing interests: The authors declare no competing interests. Compliance with ethical standards: The study was conducted in accordance with the Declaration of Helsinki and was approved by the Institutional Ethics Committee. Informed consent: The written consent was obtained from the parents of the children prior to the data collection., (© 2025. The Author(s).)

In recent years, computationally assisted diagnosis for classifying autism spectrum disorder (ASD) and typically developing (TD) individuals based on neuroimaging data, such as functional magnetic resonance imaging (fMRI), has garnered significant attention. Studies have shown that long-range functional connectivity patterns in ASD patients exhibit significant abnormalities, and individual brain networks display considerable heterogeneity. However, current graph neural networks (GNNs) used in ASD research have failed to adequately capture long-range connectivity and have overlooked individual differences. To address these limitations, this study proposes a novel multi-scale graph neural network based on biased random walks (mGNN-bw). The model introduces a co-optimization strategy between sub-models and the main model, leveraging node pooling scores from sub-models to guide biased random walks, effectively capturing long-range connectivity. By constructing high-order brain networks through path encoding and aggregation, and integrating them with low-order brain networks based on Pearson correlation, the model achieves a robust multi-scale feature representation. Experimental results on the publicly available ABIDE I dataset demonstrate the superior performance of our approach, achieving accuracy rates of 74.8% and 73.2% using CC200 and AAL atlases, respectively, outperforming existing methods. Additionally, the model identifies key ASD-associated brain regions, including the frontal lobe, insula, cingulate, and calcarine, supported by existing research. The proposed method significantly contributes to the clinical diagnosis of ASD.

Background: Brain variations are responsible for developmental impairments, including autism spectrum disorder (ASD). EEG signals efficiently detect neurological conditions by revealing crucial information about brain function abnormalities., Objective: This study aims to utilize EEG data collected from both autistic and typically developing children to investigate the potential of a Graph Convolutional Neural Network (GCNN) in predicting ASD based on neurological abnormalities revealed through EEG signals., Methods: In this study, EEG data were gathered from eight autistic children and eight typically developing children diagnosed using the Childhood Autism Rating Scale at the Central Institute of Psychiatry, Ranchi. EEG recording was done using a HydroCel GSN with 257 channels, and 71 channels with 10-10 international equivalents were utilized. Electrodes were divided into 12 brain regions. A GCNN was introduced for ASD prediction, preceded by autoregressive and spectral feature extraction., Results: The anterior-frontal brain region, crucial for cognitive functions like emotion, memory, and social interaction, proved most predictive of ASD, achieving 87.07% accuracy. This underscores the suitability of the GCNN method for EEG-based ASD detection., Conclusion: The detailed dataset collected enhances understanding of the neurological basis of ASD, benefiting healthcare practitioners involved in ASD diagnosis.

Objective: The aim of this study is to identify characteristics of children for whom a developmental-behavioral pediatrician's (DBP) diagnostic impressions of autism spectrum disorder (ASD) or non-ASD were changed by Autism Diagnostic Observation Schedule (ADOS) results., Method: A prospective study of children 1½ to <6 years consecutively referred to 8 sites for possible ASD. Cognitive/developmental, language, and adaptive testing varied, as each site followed its usual clinical approach. DBPs documented diagnosis as ASD or non-ASD and their degree of diagnostic certainty (1-10) pre- and post-ADOS. Cases where DBP diagnostic impression did not change after ADOS administration ("Stable Group," n = 314) were compared with those for whom it did change ("Changed Group," n = 35), followed by matched random sample comparisons., Results: There were no significant differences in child characteristics (age, gender, race, ethnicity, insurance, caregiver education) between the Stable and Changed groups. DBPs' diagnostic certainty was significantly lower, both pre- and post-ADOS, in the Changed versus Stable group. Change was associated with milder symptoms of ASD and less impaired language. In an age- and gender-matched comparison, significant differences remained for diagnostic certainty and severity of social communication impairments. Cognitive scores were significantly higher in the Changed Group. Because of significantly higher caregiver education and a trend toward more privately insured children among the Changed Group, samples (n = 35 each) were then matched on those characteristics, revealing the same differences for diagnostic certainty, severity of ASD symptoms, and language skills., Conclusion: Young children with milder ASD symptoms and less impaired language may benefit most from the administration of the ADOS., Competing Interests: Disclosure: W. Barbaresi reported grants from the Health Resources and Services Administration/Maternal Child Health Bureau Developmental-Behavioral Pediatric Research Network and received a supplemental grant from Health Resources and Services Administration/Maternal Child Health Bureau to support this study. DBPNet itself is supported by a grant from Health Resources and Services Administration/Maternal Child Health Bureau, during the conduct of the study. The remaining authors declare no conflict of interest., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Objective: While a growing body of evidence suggests youth with autism are at increased risk of experiencing a mental health crisis, no study has screened for crises in an outpatient setting. The current study fills this gap by examining a) the feasibility and utility of conducting routine crisis screenings; b) the psychometrics of a brief crisis screener (the Mental Health Crisis Assessment Scale-Revised; MCAS-R); and, c) the prevalence of and types of behaviors associated with crises., Method: This study was conducted at two different outpatient mental health clinics. Screenings were conducted using the MCAS-R, a 23-item parent report measure. A total of 406 youth with autism (76% Male; 72% White; M = 11.2y; SD = 3.5y), evenly divided across clinics, were screened. Seven clinicians conducted a clinical visit, which incorporated the results of the MCAS-R, to determine whether the child was in crisis., Results: Eighty percent of youth were successfully screened, suggesting crisis screening is feasible. Most parents (73%) felt the MCAS-R helped communicate concerns with the clinician; few (<6%) felt the survey was too long or upsetting. All clinicians (100%) indicated that the MCAS-R was very helpful in facilitating communication and identifying/mitigating safety concerns; although, 33% reported screenings "sometimes" interrupted clinical flow. The MCAS-R strongly aligned with clinician ratings (88% correctly classified). Twenty percent of youth met the cutoff for crisis; aggression and self-injurious behaviors were the most common reasons for crises., Conclusion: This study suggests that outpatient crisis screening via the MCAS-R is feasible, accurate, and well received by parents and clinicians., Abbreviations: ASD: Autism Spectrum Disorder; MCAS-R: Mental Health Assessment Crisis Scale-Revised; DSM-5: Diagnostic and Statistical Manual, 5 th Edition; ADOS-2: Autism Diagnostic Observation Schedule, Second Edition; ROC: Receiver Operating Curve.

High comorbidity and diagnostic overlap between autism spectrum disorder and social anxiety disorder have been documented. We examined if differences in adaptive behavior, essential for daily functioning, could differentiate these conditions among young university students. Eighty-eight autistic and 123 non-autistic undergraduates were categorized into four groups: autistic individuals: with low (n = 26)/high (n = 62) social anxiety (SA) symptoms; non-autistic: with low (n = 63)/high (n = 60) SA. The Adaptive Behavior Assessment System (ABAS) was utilized to assess three domains of adaptive skills essential for daily functioning: conceptual (academic and communication abilities), social (relationships and understanding social cues), and practical (everyday tasks such as self-care and work). Autistic students, regardless of SA level, reported ABAS scores within the low average range for the conceptual adaptive behavior domain, while non-autistic students had average scores. In terms of ABAS social adaptive behavior scores, both autistic and non-autistic groups with high levels of SA had low average scores. Conversely, those with low SA, whether autistic or non-autistic, exhibited average scores. These results were supported by the regression analyses outcomes. While autism traits and social anxiety showed medium (β=-0.37) and small (β=-0.27) effects, respectively, on conceptual adaptive scores, only social anxiety exhibited significant (medium) effects on social (β=-0.41) and practical (β=-0.34) adaptive scores. Reduced conceptual skills, previously linked to communication and executive function, may distinguish autism from social anxiety. Implications for research and practice are discussed., Competing Interests: Declaration of competing interest The authors declare no conflicts of interest related to this study. No financial, personal, or professional relationships that could influence the work reported in this manuscript have been disclosed., (Copyright © 2024 Elsevier B.V. All rights reserved.)

This case report describes a boy aged 8 years with autism spectrum disorder who was diagnosed with electrical status epilepticus in sleep (ESES) and found to have a likely pathogenic variant in the SEMA6B gene. The patient presented with developmental regression and cognitive decline. An electroencephalogram demonstrated continuous spike-and-wave discharges during sleep, a hallmark of ESES. Genetic testing identified a De Novo likely pathogenic variant in SEMA6B, a gene implicated in neurodevelopmental disorders and epilepsy. Although the association between SEMA6B mutations and ESES is not well established, this case suggests that the genetic variant may have contributed to the patient's clinical presentation. This is the first reported instance of ESES being linked to a SEMA6B gene variant, highlighting the importance of genetic testing in similar cases. The findings could have significant implications for the understanding and management of ESES in autistic patients with behavioral difficulties. They also underscore the need for further research into the role of SEMA6B in epilepsy and neurodevelopmental disorders., (Copyright © 2024 by the American Academy of Pediatrics.)

Objective: The objective of this study was to probe neuropsychological mechanisms of social communication in children with Autism Spectrum Disorders (ASD) and children with Developmental Language Disorders (DLD). Due to overlap of symptoms that include social dysfunction, diagnostic boundaries between these two developmental disorders remain unclear. This study hypothesizes that these two groups of children differ in the characteristics and in the underlying mechanisms of their social issues., Method: This study examines a wide range of neuropsychological domains in search of a relationship with social communication. A total of 75 children with ASD and 26 children with DLD are included. A cross-battery assessment of neuropsychological functions is conducted, and social communication is evaluated using the Social Responsiveness Scale (SRS)., Results: The neuropsychological profile for the ASD group differs from the DLD group, with the former demonstrating higher scores on Visual Processing and Comprehension, whereas the DLD group scores higher on Fluid Reasoning, Visual Processing and Processing Speed. Correlation analysis reveals that the association between neuropsychological domains and social communication differs between the groups., Discussion: Children with ASD and DLD clearly have distinctive neuropsychological profiles-their strengths and weaknesses are not equivalent. Such results motivate broad assessment of neuropsychological functions, as this assists in differentiating ASD from DLD for theragnostic purposes.

Purpose: To make early detection of individuals with autism spectrum disorder (ASD), caregiver-report instruments remain an efficient and adaptable option for the preliminary assessment. This study aimed to compare the psychometric properties of the Clancy Autism Behavior Scale (CABS) and Autism Behavior Checklist (ABC) as screening tools for ASD by caregivers., Methods: The data were collected from 154 pairs of children and their parents, who sought medical attention for suspected autism at Peking University Sixth Hospital. The sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio, negative likelihood ratio, Youden index, and area under the receiver operating characteristics curves (AUC) of the CABS and ABC were calculated and compared using recommended cut-off values from initial papers. The optimal cut-off values for CABS and ABC were determined according to the maximum Youden index., Results: The ABC performed better than the CABS in screening autistic persons. Specifically, the ABC demonstrated higher sensitivity than the CABS in identifying children with ASD, while the CABS exhibited superior specificity compared to the ABC. According to the maximum Youden index, the optimal cut-off value was determined to be 13 for CABS and 62 for ABC., Conclusion: The ABC exhibits higher sensitivity and overall performance in screening individuals with ASD compared to the CABS. The ABC is more suitable as a screening tool for caregivers in both domestic and clinical settings, while the CABS may be utilized when evaluation time or medical resources are limited due to its shorter completion time and fewer items., Competing Interests: Declarations. Ethics Approval: Approval was obtained from the ethics committee of Peking University Sixth Hospital. The procedures used in this study adhere to the tenets of the Declaration of Helsinki. Informed Consent: was obtained from all individual participants included in the study. Conflict of Interest: All authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest or non-financial interest in the subject matter or materials discussed in this manuscript., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Background: Sleep problems are reported for up to 80% of autistic individuals. We examined whether parsimonious sets of items derived from the Modified Checklist for Autism in Toddlers, Revised (M-CHAT-R) and the Brief Infant Sleep Questionnaire (BISQ) are superior to the standard M-CHAT-R in predicting subsequent autism spectrum disorder (ASD) diagnoses., Methods: Participants from 11 Environmental influences on Child Health Outcomes (ECHO) cohorts were included. We performed logistic LASSO regression models with 10-fold cross-validation to identify whether a combination of items derived from the M-CHAT-R and BISQ are superior to the standard M-CHAT-R in predicting ASD diagnoses., Results: The final sample comprised 1552 children. The standard M-CHAT-R had a sensitivity of 44% (95% CI: 34, 55), specificity of 92% (95% CI: 91, 94), and AUROC of 0.726 (95% CI: 0.663, 0.790). A higher proportion of children with ASD had difficulty falling asleep or resisted bedtime during infancy/toddlerhood. However, LASSO models revealed parental reports of sleep problems did not improve the accuracy of the M-CHAT-R in predicting ASD diagnosis., Conclusion: While children with ASD had higher rates of sleep problems during infancy/toddlerhood, there was no improvement in ASD developmental screening through the incorporation of parent-report sleep metrics., Impact: Parental-reported sleep problems are common in autism spectrum disorder (ASD). We investigated whether the inclusion of parental-reports of infant/toddler sleep patterns enhanced the effectiveness of developmental screening for autism. We reported higher rates of difficulty falling asleep and resisting bedtime during infancy and toddlerhood among children later diagnosed with ASD; however, we did not find an improvement in ASD developmental screening through the incorporation of parent-report sleep metrics. In our sample, the standard M-CHAT-R had a sensitivity of 39% among children of mothers with government insurance compared with a sensitivity of 53% among children of mothers with employer-based insurance., Competing Interests: Competing interests: The authors declare no competing interests. Consent to participate: The study protocol was approved by the single ECHO institutional review board, WCG IRB. Written informed consent or parent’s/guardian’s permission was obtained along with child assent as appropriate, for the ECHO Cohort Data and Biospecimen Collection Protocol participation and for participation in specific study sites., (© 2024. The Author(s), under exclusive licence to the International Pediatric Research Foundation, Inc.)

Background: Since 2001, the American Academy of Pediatrics has released and twice revised guidelines tasking paediatricians with screening children for developmental disorders, but diagnoses are often delayed. Paediatricians in the United States are also responsible for referring patients with identified concerns for services and for managing their long-term care., Objectives: This review aims to chronologically synthesize available literature about paediatricians' perspectives surrounding their roles in identifying and managing early childhood disorders and to identify how future interventions can best address these perspectives., Methods: Early childhood disorders (ECDs) were defined as developmental delays and autism spectrum disorder. A literature search was performed on PubMed and Google Scholar. Surveys, interviews, focus groups and analyses of paediatricians' perspectives on their roles in identifying and managing children with ECDs were included if they were performed in the United States and published in a peer-reviewed journal in or after 2001. Literature was reviewed and analysed by sorting key findings into categories of 'knowledge', 'attitudes' and 'confidence', then organizing chronologically within each category., Results: Of the 122 publications identified, 19 were selected and reviewed, revealing some overlying themes. First, paediatricians desire more training on ECDs, especially in assisting with navigation of intervention programs. Second, negative attitudes towards roles in identifying and managing ECDs have remained relatively consistent since 2001. Third, paediatricians' confidence declines from identification to long-term management of ECDs., Conclusions: This review chronologically synthesizes paediatricians' knowledge, attitudes and confidence surrounding their roles in identifying children with ECDs, referring them to other professionals and managing their long-term care. Paediatricians are not solely responsible for these tasks, as other medical professionals, families, therapists and educators work together to care for these children. This review provides recommendations, such as enhancing training programs and utilizing care coordinators, to address perspectives that may result in suboptimal patient care., (© 2025 John Wiley & Sons Ltd.)

Autism Spectrum Disorder (ASD) is a multifaceted neurodevelopmental condition marked by challenges in social communication, sensory processing, and behavioral regulation. The delayed diagnosis of ASD significantly impedes timely interventions, which can exacerbate symptom severity. With approximately 62 million individuals affected worldwide, the demand for efficient diagnostic tools is critical. This study introduces a novel framework that combines a White Shark Optimization (WSO)-based feature selection method with a Bidirectional Long Short-Term Memory (Bi-LSTM) classifier for enhanced autism classification. Utilizing the WSO technique, we identify key features from autism screening datasets, which markedly improves the model's predictive capabilities. The optimized feature set is then processed by the Bi-LSTM classifier, enhancing its efficiency in handling sequential data. We comprehensively address methodological challenges, including overfitting, generalization, interpretability, and computational efficiency. Furthermore, we conduct a comparative analysis against baseline algorithms such as Neural Networks, Convolutional Neural Networks (CNN), and Long Short-Term Memory (LSTM) networks, while also employing Particle Swarm Optimization (PSO) for feature selection validation. We evaluate performance metrics, including accuracy, F1-score, specificity, precision, and sensitivity across three ASD datasets: Toddlers, Adults, and Children. Our results demonstrate that the WS-BiTM model significantly outperforms baseline methods, achieving accuracies of 97.6 %, 96.2 %, and 96.4 % on the respective datasets. Additionally, we implemented leave-one-dataset cross-validation and confirmed the statistical significance of our findings through a paired t-test, supplemented by an ablation study to detail the contributions of individual model components. These findings highlight the potential of the WS-BiTM model as a robust tool for ASD classification., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Objective: Autism diagnosis is fraught with inequities, including misdiagnosis and delayed identification that disproportionately affect minoritized youth. Aspects of clinician decision-making, particularly diagnostic certainty, may contribute to these inequities. Little is known about how closely clinician certainty corresponds with autistic traits, nor whether certainty relates to socio-demographic factors., Method: Autistic youth from the Simons Simplex Collection ( N  = 2,853) completed assessments after which clinicians rated how certain they were that the child met autism diagnostic criteria. Core clinical factors included clinician-observed (Autism Diagnostic Observation Schedule; ADOS) and parent-reported autistic traits (Social Communication Questionnaire), and an overall IQ score., Results: Clinician certainty was moderately positively associated with parent-reported and observed autistic traits and was just as strongly negatively associated with IQ. Socio-demographic factors significantly associated with certainty, even accounting for clinical measures. Lower income and older child age related to less certainty. In contrast, clinicians rated higher certainty for youth identified as Hispanic, Black or African American, or Asian. Race and income also moderated the concordance between certainty with clinical factors. The agreement between higher ADOS scores and higher certainty was significantly weaker for lower-income families. The association between lower IQ and higher certainty was non-significant for Asian youth., Conclusions: Diagnostic certainty ratings do not necessarily correspond closely with the level of autistic traits, and clinician perception of autism diagnosis may be related to demographic factors. Caution is needed when relying on clinician certainty to inform diagnosis. Future research on diagnostic practices is urgently needed among diverse and minoritized communities.

Assessment for autism spectrum disorder (ASD) in the pediatric female population entails unique diagnostic complexities. Females are often misdiagnosed, undiagnosed, or receive an ASD diagnosis at a later age than males. Male bias in ASD, masking behaviors, cultural norms, and overlapping neurodevelopmental comorbidities (such as attention deficit/hyperactivity disorder and intellectual disability) contribute to this phenomenon. The authors present two clinical cases evaluated in an interdisciplinary developmental behavioral pediatrics (DBP) team to highlight these considerations. Cases describe adolescent and school aged females with medical complexity who did not initially appear to have ASD symptoms but later were diagnosed with ASD. Patient anonymity is preserved. Best practice recommendations are discussed. Shared decision making, intentional history taking, thorough observation of behavior and restrictive/repetitive/sensory interests in multiple settings, and attention to social communication in the context of cognitive capacity are essential for ASD assessment in pediatric females., Competing Interests: CONFLICTS OF INTEREST We have no known conflict of interest to disclose., (Copyright © 2024 National Association of Pediatric Nurse Practitioners. Published by Elsevier Inc. All rights reserved.)

Lay Abstract: Primary care providers often screen for autism during well child visits in the first few years of life and refer children for diagnostic evaluations when needed. However, most children do not receive a diagnosis until years later which delays access to services. Racism, socioeconomic status, and other systemic inequalities that limit access to health care further delay diagnostic evaluations. Mental health clinicians who work in primary care clinics can help address barriers to accessing diagnostic evaluation services once they are recommended by their primary care provider. However, mental health clinicians who work in primary care typically do not have training in diagnosing autism. The goal of this study was to evaluate a program training mental health professionals working in an urban primary care setting, primarily serving Black and Latinx families insured by Medicaid, to provide autism diagnostic evaluations. Two hundred and fifty children completed evaluations through the Autism in Primary Care (APC) program. The wait time to access an evaluation through APC was significantly shorter than through standard avenues of care (e.g. referring to a separate autism clinic). Referring primary care providers and caregivers endorsed high levels of satisfaction with the program. Conducting autism evaluations in primary care settings offers a promising opportunity to improve earlier diagnosis and treatment access for families, reduce inequities in care, and increase caregiver and child well-being.