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Early intervention (EI) based on behavioral science is one of the most promising treatment options for children with autism. Ever since Ivar Lovaas study from 1987, researchers are aware of the benefits of intensive early intervention in improving the outcomes of children with autism. Children who receive EI often show remarkable improvements in their social, cognitive, and adaptive skills. These interventions typically involve structured teaching methods, intensive behavioral therapies, and a variety of support services tailored to the individual needs of each child. By addressing the core symptoms of autism early in a child's development, these programs aim to foster better longterm outcomes. In this paper, we presented an overview of the main topics in the field of EI for children with autism published in major scientific journals. For this purpose, we performed a search of the Web of Science citation base and identified 91 articles published in the period 2019-2023 that had the words "early intervention" and "autism" OR "ASD" in their titles. The selected articles dealt with several interesting topics ranging from improving social communication and joint attention to topics dealing with quality of life and parent mediated EI programs. We concluded the paper with a discussion on the future directions of EI research. Despite the significant progress made, there is still much to learn about optimizing these early behavior interventions. Future research should aim to personalize intervention strategies to meet the unique needs of each child with autism and their families. Additionally, more longitudinal studies are needed to understand the long-term impacts of EI on various life outcomes. [ABSTRACT FROM AUTHOR]

This review explores the clinical presentation of similarities and differences in Attention-Deficit/Hyperactivity Disorder (ADHD) and Autism Spectrum Disorder (ASD). This paper investigates the deficits in executive function, social function, and emotional intelligence that are seen in both conditions and how the presence of both conditions can exacerbate these deficiencies. Understanding the clinical presentations in these domains is critical to refine diagnostic methods and treatments and improve outcomes for those affected by these neurodevelopmental disorders. The similarities in clinical presentation between ADHD and ASD present a significant diagnostic challenge, with individuals often exhibiting similar behaviors and difficulty navigating the complexities that encompass reacting to their environment. Further research is paramount in gaining more knowledge of the disorders and challenges faced by these individuals, especially those with the presence of both conditions. [ABSTRACT FROM AUTHOR]

Background: Receiving a child's autism diagnosis can be stressful; as such, parent resolution contributes to the wellbeing and development of healthy parent-child relationships. In other significant childhood diagnoses (e.g., cerebral palsy, diabetes), the degree to which parents adjust to (a) their child's diagnosis and (b) their changes in expectations concerning their child's development and capacity (referred to as resolution to diagnosis), has been associated with improved outcomes including facilitating parent-child relationships and improved parental wellbeing. Given potential benefits to parent and child, and the heterogenous nature of autism, examining the unique factors associated with resolution to diagnosis is important. In this systematic review we identified factors that support or inhibit parental resolution to their child receiving a diagnosis of autism. Methods: We completed a systematic review following PRISMA guidelines of peer-reviewed studies from2017 to 2022, that investigated parental resolution or acceptance of an autism diagnosis. Papers including "acceptance" needed to encompass both accepting the diagnosis and the implications regarding the child's abilities. We searched six databases (Scopus, Web of Science, MEDLINE, PsycINFO, ProQuest), with additional papers located following review of reference lists. Results: Fourteen papers with 592 participants that investigated parental resolution or acceptance of an autism diagnosis, were included. We identified six common factors that facilitate or inhibit parental resolution and acceptance of an autism diagnosis including: symptom severity; religion, belief, and culture; knowledge and uncertainty; negative emotions (i.e., denial, shame, guilt); positive emotions; and support. Greater resolution was associated with improved "attunement and insightfulness" in the parent-child relationship. Limitation: The review was limited by the small number of studies meeting inclusion criteria. Second, the quality of included studies was mixed, with over half of the studies being qualitative and only one randomized control trial (RCT) identified. Conclusion: Parental resolution can have an impact on parent's perception of their child's capabilities and impact the parent-child relationship. We identified six categories that aid in inhibiting or promoting resolution to diagnosis. Despite taking a broad approach on the definition of resolution, the low number of studies identified in the review indicates a need for more research in this area. [ABSTRACT FROM AUTHOR]

Background: Over the past years, researchers have been using head-mounted eye-tracking systems to study young children's gaze behaviors in everyday activities through which children learn about the world. This method has great potential to further our understanding of how millisecond-level gaze behaviors create multisensory experiences and fluctuate around social environments. While this line of work can yield insight into early perceptual experiences and potential learning mechanisms, the majority of the work is exclusively conducted with typically-developing children. Sensory sensitivities, social-communication difficulties, and challenging behaviors (e.g., disruption, elopement) are common among children with developmental disorders, and they may represent potential methodological challenges for collecting high-quality data. Results: In this paper, we describe our research practices of using head-mounted eye trackers with 41 autistic children and 17 children with increased likelihood of later autism diagnosis without auditory or visual impairments, including those who are minimally or nonspeaking and/or have intellectual disabilities. The success rate in gathering data among children with autism was 92.68%. 3 of 41 children failed to complete the play-session, resulting in an 86.36% success rate among 1–4-year-olds and a 100.00% success rate among 5–8-year-olds. 1 of 17 children with increased likelihood of later autism diagnosis failed to complete the play-session, resulting in a success rate of 94.11%. There were numerous "challenging" behaviors relevant to the method. The most common challenging behaviors included taking the eye-tracking device off, elopement, and becoming distressed. Overall, among children with autism, 88.8% of 1–4-year-olds and 29.4% of 5–8-year-olds exhibited at least one challenging behavior. Conclusions: Research capitalizing on this methodology has the potential to reveal early, socially-mediated gaze behaviors that are relevant for autism screening, diagnosis, and intervention purposes. We hope that our efforts in documenting our study methodology will help researchers and clinicians effectively study early naturally-occuring gaze behaviors of children during non-experimental contexts across the spectrum and other developmental disabilities using head-mounted eye-tracking. Ultimately, such applications may increase the generalizability of results, better reflect the diversity of individual characteristics, and offer new ways in which this method can contribute to the field. [ABSTRACT FROM AUTHOR]

Children with autism spectrum disorder (ASD) have deficits that affect their social relationships, communication, and flexibility in reasoning. There are different types of treatment (pharmacological, educational, psychological, and rehabilitative). Currently, one way to address this problem is by using robotic systems to address the abilities that are altered in these children. The aim of this review will be to analyse the effectiveness of the incorporation of the different robotic systems currently existing in the treatment of children up to 10 years of age diagnosed with autism. A systematic review has been carried out in the PubMed, Scopus, Web of Science, and Dialnet databases, with the following descriptors: child, autism, and robot. The search yielded 578 papers, and nine were selected after the application of the PRISMA guideline. The quality of the studies was analysed with the PEDRo scale, and only those with a score between four and six were selected. From this study, the conclusion is that the use of robots, in general, improves children's behaviour in the short term, but longer-term experiences are necessary to achieve more conclusive results. [ABSTRACT FROM AUTHOR]

This paper highlights one of the most critical aspects of facilitating vocabulary learning among children with autism. Several pertinent issues serve as the focus of the paper; vocabulary course design for high functioning children with autism and the relevant considerations required when teaching them using technology. To explore these issues, a qualitative design using content analysis through extensive literature review was conducted. The content analysis included a critical examination of the features of children with autism and their learning and the theories of vocabulary course design and its principles. The analysis brought to light relevant considerations following the five factors as identified from the critical examination of the literature. Hence, this paper proposes course design for high functioning children with autism considerations. Curriculum designers, syllabus writers and instructors for children with autism could expect to benefit from this paper. This paper also recommends quantitative research such as a survey with the relevant stakeholders to confirm or enrich the data from the present study. [ABSTRACT FROM AUTHOR]

Increased number of children with autism spectrum disorder (ASD) has also heightened interest in finding and providing appropriate interventions. Early intervention is implemented at the moment when deviations are noticed, without waiting for an official diagnosis. Parents are crucial participants in interventions carried out with children; therefore, this research considers interventions focused on training parents to work with children with ASD up to the age of six. For the purposes of this paper, we searched the following journals: Autism, Focus on Autism and Other Developmental Disabilities, and Research in Autism. The search was limited to editions from 2012 to 2022, and the following keywords were considered: parent training, early intervention, autism. References were searched manually. The initial search yielded a total of 992 articles. Twenty-four studies related to children up to six years old and involving parent training in early intervention were included in the analysis. Using a tool for assessing quantitative studies, the selected studies were evaluated, with each component assessed based on the information contained in the study as good, moderate, or weak. The overall rating for the paper can be strong, moderate, or weak. This paper highlights the importance of support to enhance parental competencies. [ABSTRACT FROM AUTHOR]

Aim: To compare the efficacy of 0, 5, and 20 sessions of transcranial direct current stimulation (tDCS) for reducing symptoms of autism spectrum disorder (ASD). Method: Thirty‐six male children with ASD (mean age 2 years 3 months, SD 4 months, age range 1 years 6 months–2 years 11 months) were balanced and stratified by age, sex, and baseline severity of ASD, to: (1) a control group that received 20 sessions of sham tDCS; (2) a 5‐session tDCS group (5‐tDCS) that received 5 sessions of active tDCS followed by 15 sessions of sham tDCS; and (3) a 20‐session tDCS group (20‐tDCS) that received 20 sessions of active tDCS. All groups participated in the special school activity of Khon Kaen Special Education Center, Thailand. The primary outcome was autism severity as measured by the Childhood Autism Severity Scale. Results: The 5‐tDCS and 20‐tDCS groups evidenced greater reductions in autism severity than the control group at days 5 and 14, and months 6 and 12. There were no significant differences in the outcome between the 5‐ and 20‐tDCS groups at any time point. Within‐group analysis showed clinically meaningful improvements starting at month 6 for the participants in the control group, and clinically meaningful improvements starting on day 5 in both active tDCS groups, all of which were maintained to month 12. Interpretation: The 5‐ and 20‐session tDCS seems to reduce autism severity faster than sham tDCS. These effects maintained at least for 1 year. What this paper adds: Twenty sessions of transcranial direct current stimulation (tDCS) were not superior to five sessions.Sham tDCS with a special school activity can reduce autism severity starting at 6 months after treatment.The benefits observed for 5 and 20 sessions of tDCS last for at least 12 months. What this paper adds: Twenty sessions of transcranial direct current stimulation (tDCS) were not superior to five sessions.Sham tDCS with a special school activity can reduce autism severity starting at 6 months after treatment.The benefits observed for 5 and 20 sessions of tDCS last for at least 12 months. This original article is commented on by Wilson on pages 730–731 of this issue. [ABSTRACT FROM AUTHOR]

Autism spectrum disorder (ASD) is diagnosed based on socio-communicative difficulties, which are believed to result from deficits in mentalizing, mainly evidenced by alterations in recognizing and responding to the mental states of others. In recent years, efforts have been made to develop mentalization-based treatment (MBT) models for this population. These models focus on enhancing individuals’ ability to understand and reflect on their own mental states, as well as those of others. However, MBT approaches for people with ASD are limited by their existing theoretical background, which lacks a strong foundation grounded in neuroscience-based evidence properly integrated with attachment, and mentalizing. These are crucial aspects for understanding psychological processes in autism, and as such, they play a pivotal role in shaping the development of tailored and effective therapeutic strategies for this specific population. In this paper we review evidence related to the neurobiological, interpersonal, and psychological dimensions of autism and their implications for mentalizing processes. We also review previous mentalization-based frameworks on the psychosis continuum to provide a comprehensive understanding of attachment, neurobiology, and mentalization domains in therapeutic approaches for autism. After presenting a synthesis of the literature, we offer a set of clinical strategies for the work with children with autism. Finally, we provide recommendations to advance the field towards more robust models that can serve as a basis for evidence-based therapeutic strategies. [ABSTRACT FROM AUTHOR]

Human pose estimation has important applications in medical diagnosis (such as early diagnosis of autism in children and assisting with the diagnosis of Parkinson's disease), human-computer interaction, animation, and other fields. Currently, many human pose estimation algorithms are based on deep learning. However, most research focuses only on increasing the depth and width of the network model. This approach overlooks that merely enlarging the network's depth and width results in excessive parameterization, without enhancing the model's effective receptive field or its ability to extract multi-scale features. Hence, this paper constructs a network model, named MS-HRNet (Multi-Scale High-Resolution Network), for human pose estimation. Specifically, we propose a more concise and efficient version of HRNet framework as the backbone network of MS-HRNet. This addresses the challenges of HRNet complex structure and large number of parameters that cause training difficulties, and its inadequacy in handling multi-scale information. Additionally, we designed a multi-scale convolutional kernel parallel module named MSBlock (Multi-Scale Block) as the basic block of MS-HRNet. By introducing coordinate attention modules and ASFF (Adaptive Spatial Feature Fusion) modules, the model's ability to extract information is effectively increased, and the issue of feature conflict during the fusion of features with different resolutions is resolved, with only a small increase in the number of model parameters. To evaluate the effectiveness of the proposed model, we conducted comparison experiment and ablation experiments using popular human pose estimation datasets, including COCO2017 and MPII, against multiple existing human pose estimation models.On the COCO 2017 dataset, the number of MS-HRNet parameters are decreased by 41% than the baseline model HRNet, the computational complexity by 59%, and the detection accuracies(mAP) are increased by 2.4 point. [ABSTRACT FROM AUTHOR]

The present impact of the COVID-19 pandemic on families of Autism children's, Caregivers play a major role and caring for the individual of autism spectrum disorder (ASD) children's in ideal circumstances, and it can be a stressful and high degree of disturbance in life. The purpose of this empirical research paper is to examine the Depression, Anxiety, and Stress of caregivers of autism children at three special schools in Chennai. The objectives of the paper are to describe the socio-demographic characteristic of the respondents to measure the level of depression, anxiety, andstress among respondents and to find out the statistically significant relationship/differencebetween selected socio-demographic Characteristic of Respondents and dependent variables. A descriptive research design has adopted. The universe of the paper consists of caregivers of autism children who are studying at three special schools in Chennai, there are about 150 Special children are studying in three special schools, out of these, 60 caregivers of autism children were selected as a sample by adopting simple random sampling using lottery method and a semi -structured questionnaire was prepared in order to understand the socio-demographic characteristic of the respondents along with DASS-42 items was used. The questionnaire method was adopted. The collected data has been analyzed using Statistical Package for Social Science version 20. The study results are revealed in Section VI of Results. [ABSTRACT FROM AUTHOR]

Increased number of children with autism spectrum disorder (ASD) has also heightened interest in finding and providing appropriate interventions. Early intervention is implemented at the moment when deviations are noticed, without waiting for an official diagnosis. Parents are crucial participants in interventions carried out with children; therefore, this research considers interventions focused on training parents to work with children with ASD up to the age of six. For the purposes of this paper, we searched the following journals: Autism, Focus on Autism and Other Developmental Disabilities, and Research in Autism. The search was limited to editions from 2012 to 2022, and the following keywords were considered: parent training, early intervention, autism. References were searched manually. The initial search yielded a total of 992 articles. Twenty-four studies related to children up to six years old and involving parent training in early intervention were included in the analysis. Using a tool for assessing quantitative studies, the selected studies were evaluated, with each component assessed based on the information contained in the study as good, moderate, or weak. The overall rating for the paper can be strong, moderate, or weak. This paper highlights the importance of support to enhance parental competencies [ABSTRACT FROM AUTHOR]

The notion of a connection between autism and music is as old as the first reported cases of autism, and music has been used as a therapeutic tool for many decades. Music therapy holds promise as an intervention for individuals with autism, harnessing their strengths in music processing to enhance communication and expression. While previous randomized controlled trials have demonstrated positive outcomes in terms of global improvement and quality of life, their reliance on psychological outcomes restricts our understanding of underlying mechanisms. This paper introduces the protocol for the Music for Autism study, a randomized crossover trial designed to investigate the effects of a 12-week music therapy intervention on a range of psychometric, neuroimaging, and biological outcomes in school-aged children with autism. The protocol builds upon previous research and aims to both replicate and expand upon findings that demonstrated improvements in social communication and functional brain connectivity following a music intervention. The primary objective of this trial is to determine whether music therapy leads to improvements in social communication and functional brain connectivity as compared to playbased therapy. In addition, secondary aims include exploring various relevant psychometric, neuroimaging, and biological outcomes. To achieve these objectives, we will enroll 80 participants aged 6-12 years in this international, assessor-blinded, crossover randomized controlled trial. Each participant will be randomly assigned to receive either music therapy or play-based therapy for a period of 12 weeks, followed by a 12-week washout period, after which they will receive the alternate intervention. Assessments will be conducted four times, before and after each intervention period. The protocol of the Music for Autism trial provides a comprehensive framework for studying the effects of music therapy on a range of multidimensional outcomes in children with autism. The findings from this trial have the potential to contribute to the development of evidence-based interventions that leverage strengths in music processing to address the complex challenges faced by individuals with autism. [ABSTRACT FROM AUTHOR]

Evolutionary computing algorithms are computational intelligent systems that are used in a wide range of research applications, primarily for optimization. In this paper, an artificial neural network (ANN), a machine learning technique, is used to classify the data. The weights associated with each neuron and the architecture of the neural network always bias the output of the network model. With prior knowledge or trial and error techniques, different metrics or objectives can be used to optimise these weights. The optimization of weights using multiple objectives refers to a "multi-objective optimization problem." In this paper, an evolutionary cultural algorithm is used to optimise weights in ANN, and the results are reported with improved accuracy. Three benchmark datasets for autism screening data are used, trained, and tested for model accuracy in the classification: toddlers (1054,19), children (292,21), and adults (704,21).With the support of the domain expert, real-time data were collected from parents and caregivers and totalled over 1000 records, with a moderate difference in attributes based on CARS-2 (Childhood Autism Rating Scale, 2nd Edition) for ASD screening. In this paper, the proposed model is compared using a curve-fitting mathematical technique. The proposed model is trained and tested, and the results showed that it outperformed other algorithms in terms of precision, accuracy, sensitivity, and specificity. [ABSTRACT FROM AUTHOR]

Autism is a serious and widespread developmental disorder in children. With the increase of autistic children every year, it is necessary to study a set of effective music therapy activities that can penetrate into life to help autistic children's rehabilitation training. This paper aims to study the behavioral training of high-functioning autistic children with music therapy intervention under intelligent health monitoring. The autistic children were selected and divided into experimental group and control group. According to the psychological and physiological characteristics of five autistic children aged 5-7 years in the experimental group, the music therapy activity plan was designed, and the experimental intervention was carried out by combining individual music therapy and group music therapy. Compared with the control group, this paper explores the effect of music on the treatment of children with autism. The experimental results of this paper show that the language, social, cognitive, and behavioral problems of autistic children under music therapy under intelligent health monitoring have been significantly improved, and their emotional response ability has improved the most, increasing by 34%. Communication ability was next, increased by 20.3%; motor coordination ability increased by 20%; and cognitive ability improved by 11%. It can be explained that the four aspects of language, social interaction, cognition, and behavior have been significantly improved after music therapy. [ABSTRACT FROM AUTHOR]

Autism spectrum disorder (ASD), is a neurological developmental disorder. It affects how people communicate and interact with others, as well as how they behave and learn. The symptoms and signs appear when a child is very young. Derived with increased usage of machine learning procedure in the medicinal analysis investigations. In this paper, our objective is to find out the most significant attributes and automate the process using classification techniques and pattern clustering using K-means clustering. We have analyzed ASD datasets of children towards determining the best performance of classifier for these binary datasets considering recall, precision, accuracy and classification errors. For this purpose only we use classifier along with a training model with the deep learning technique. In this deep neural network the different types of patterns have been obtained, and then the entire autism dataset has been trained using this classification technique. After that, the group of patterns has been formed using K- means clustering technique. Then these grouped patterns have been sent to the stochastic gradient descent (SGD) for obtaining the classification with enhanced accuracy, and after this, the regression process is done, then by this classified output, the recommendation learning system model is given for autism affected children. The need for recommendation for ASD is due to slow functioning of the brain and change in personal characteristic of the affected children, so it is necessary for recommendation learning model in ASD. [ABSTRACT FROM AUTHOR]

In this paper, we introduce a deep learning model to classify children as either healthy or potentially having autism with 94.6% accuracy using Deep Learning. Patients with autism struggle with social skills, repetitive behaviors, and communication, both verbal and non-verbal. Although the disease is considered to be genetic, the highest rates of accurate diagnosis occur when the child is tested on behavioral characteristics and facial features. Patients have a common pattern of distinct facial deformities, allowing researchers to analyze only an image of the child to determine if the child has the disease. While there are other techniques and models used for facial analysis and autism classification on their own, our proposal bridges these two ideas allowing classification in a cheaper, more efficient method. Our deep learning model uses MobileNet and two dense layers to perform feature extraction and image classification. The model is trained and tested using 3,014 images, evenly split between children with autism and children without it; 90% of the data is used for training and 10% is used for testing. Based on our accuracy, we propose that the diagnosis of autism can be done effectively using only a picture. Additionally, there may be other diseases that are similarly diagnosable. [ABSTRACT FROM AUTHOR]

Background and Objectives: There is a paucity of research studies, especially from the low- and middle-income countries, on gender-specific clinical profiles of autism and whether this lack of information is a barrier for early diagnosis among females. The present paper examined the gender differences in the timing of identification of autism among children. Methods: The case records diagnosed children with autism spectrum disorder with no documented intellectual disability (IQ <70) were retrospectively analyzed. The demographic and clinical characteristics such as the presence of repetitive behaviors, deficits/delays in language, social-emotional reciprocity impairments, history of developmental regression, presence of hyperactivity, and self-injurious behaviors were extracted from the case files. Gender differences in the timing of identification, clinical characteristics, and sociodemographic variables were examined by utilizing the t-test. Results: A total of 309 case records (Mean = 5.04 years, standard deviation = 2.50) were retrieved. Girls, as compared to boys, were significantly less likely to show restricted and repetitive behaviors (X² = 3.92, P = 0.048) and showed greater socio-emotional reciprocity despite a similar level of autism severity (X² = 4.48, P = 0.034). No sex differences were found in hyperactivity, self-injurious behavior, history of developmental regression, and severity of autism (all P > 0.05). There was a significant difference in the timing of the identification of autism by gender and females were found to be identified at significantly older ages relative to males (t = 2.13, P = 0.034). Conclusions: There is an imperative need to develop more gender-sensitive diagnostic tools incorporating the sex-specific differences in clinical presentation to improve the assessment of autism in girls. [ABSTRACT FROM AUTHOR]

In this review paper, the adverse drug effect in autism children is studied after consuming the prescribed drug dosage level suggested by Physicians through computer vision-based physiological monitoring. The prescription of drug and dosage level for the autism children is done after clinical signs such as repetitive behaviour, dyspraxia, abnormal gait, and abnormality of motor functions for accurate prescription of drug dosage level. Autism children need more effective and continuous monitoring for assessment and measurement of clinical signs. The continuous and effective monitoring of autism children for the clinical sign is a challenging task for any physician. In this paper, the above problem-solve through the Drug Based Autism Child Repetitive Behaviour Estimation (DARBE) method, which is continuous monitoring of the autistic child by a thermal imaging system. Thermal imaging captures the autistic child repetitive behaviour analysis, spatial temperature levels are recorded for measurements such as Mood assessment, heart rate, and variability, finger temperature, and the temperature of the skin. The thermal imaging and logistic regression predicts the clinical signs of autistic children through thermal video processing for accurate dosage level perception and avoids adverse drug effects because of over/under dosage level of drugs. [ABSTRACT FROM AUTHOR]

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(1) Background: Augmented reality is no less popular than virtual reality. This technology has begun to be used in education fields, one of which is special education. Merging the real and virtual worlds is the advantage of augmented reality. However, it needs special attention in making software for children with special needs, such as children with autism. This paper presents an application prototype by paying attention to the characteristics of autistic individuals according to the Autism Guide, that has existed in previous studies. (2) Method: The method used in the development of this prototype is the Linear Sequential Model. Application development is made using Unity3D, Vuforia, and Adobe Illustrator by considering accessibility and other conveniences for developers. (3) Results: The prototype was developed with reference to the Autism Guide, then validated by media experts and autistic experts with the results of the assessment obtaining a score of 87.3/100 which is in the "Very Good" category and is suitable for use. (4) Conclusions: The development of a prototype that refers to the characteristics of children with autism needs to be considered so that what will be conveyed can be easily accepted. [ABSTRACT FROM AUTHOR]

The article reports on the move by "The Lancet" journal to retract on February 2, 2010 the article "Illeal-Lymphoid-Nodular Hyperplasia, Non-Specific Colitis, and Pervasive Development Disorder in Children" by Andrew Whitfield et al published in its 1998 issue. The paper proposed a link between the measles-mumps-rubella (MMR) vaccine and autism. As a result, vaccination in Great Britain declined significantly and cases of measles and mumps rose. Whitfield did not disclose that he was paid by a group of solicitors seeking evidence against vaccine makers.

The inclusion of children with autism spectrum disorder (ASD) in typical educational settings has only recently gained momentum in Greece, responding to the recommendations of the international conventions. Reform of special education legislation spotlights the inclusion of children with autism in mainstream schools. The principal goal is to accept the diversity and heterogeneity of all students. This paper presents the educational policy for children with ASD in Greece and comments on teachers' perceptions of inclusion. School closures due to the COVID-19 pandemic had an adverse impact on children's lives and created a new environment with different demands for educational inclusion. [ABSTRACT FROM AUTHOR]

The automatic emotion recognition domain brings new methods and technologies that might be used to enhance therapy of children with autism. The paper aims at the exploration of methods and tools used to recognize emotions in children. It presents a literature review study that was performed using a systematic approach and PRISMA methodology for reporting quantitative and qualitative results. Diverse observation channels and modalities are used in the analyzed studies, including facial expressions, prosody of speech, and physiological signals. Regarding representation models, the basic emotions are the most frequently recognized, especially happiness, fear, and sadness. Both single-channel and multichannel approaches are applied, with a preference for the first one. For multimodal recognition, early fusion was the most frequently applied. SVM and neural networks were the most popular for building classifiers. Qualitative analysis revealed important clues on participant group construction and the most common combinations of modalities and methods. All channels are reported to be prone to some disturbance, and as a result, information on a specific symptoms of emotions might be temporarily or permanently unavailable. The challenges of proper stimuli, labelling methods, and the creation of open datasets were also identified. [ABSTRACT FROM AUTHOR]

Autism affects how people perceive and make sense of the world around them. Autism is a spectrum condition which impacts people in different ways. Also referred to as Autism Spectrum Disorder (ASD), it is characterized by challenges in the domains of social, cognitive and motor functioning, which differ in severity. Previous research suggests that music can have cognitive, psychosocial, behavioural, and motor benefits in this population. We systematically review the use of technology in Music-therapy and related sound-based activities to improve the motor and social skills of children. In May 2020 we conducted a systematic search on Music-therapy and musical activities for autistic children in research databases including Science Direct, APA PsycNet, Cochrane, IEE andWeb of Science, to collect relevant studies. We initially collected 5179 papers of which only 27 studies were identified as suitable for the scope of this review. In the paper, we analyse and describe key characteristics of each project. We then highlight the commonalities, strengths and limitations of existing work, and identify implications for future interaction design. [ABSTRACT FROM AUTHOR]

The pathology of autism dates back to the 1900s, being framed within the broad sphere of neuropsychological conditions. So far, the autism spectrum disorder (ASD) has passed through various pathologies, from socio-emotional disorders to schizophrenic disorders. The clear distinction between childhood autism and childhood schizophrenia was only made in the early 1980s. ASD is one of the most common invasive developmental disorders; defined as a neurological condition characterised by a distortion in the overall development of a person, it affects 1 in 150 children and 4 to 5 boys per girl. The autistic triad brings together qualitative anomalies in social interactions (in verbal and nonverbal communication), restricted interests and stereotypes. The 1980s and 1990s highlight the role of behavioural therapy and the use of highly controlled learning environments as a primary treatment for the forms of autism and related conditions. Promising studies on the role of oxytocin or certain amino acids involved in neurotransmission, especially in regulating stress and its emotional consequences, are currently in progress. Until now, the two therapies have remained primordial along with physical therapy and speech therapy. The purpose of this paper is to present some of the means that can contribute to the pre-integration of children in mainstream education, being also a starting point for future applied research. At the same time, the paper is helpful for the parents of children with ASD, who are given the opportunity to work themselves in the absence of a specialist or financial possibilities. [ABSTRACT FROM AUTHOR]

There is controversy as to whether children with developmental language disorder (DLD) and those with high-functioning autism plus language impairment (HFA-LI) share similar language profiles. This study investigated the similarities and differences in the production of Chinese negative sentences by children with DLD and children with HFA-LI to provide evidence relevant to this controversy. The results reflect a general resemblance between the two groups in their lower-than-TDA (typically developing age-matched) performance. Both groups encountered difficulties in using negative markers, which suggests that they might be impaired in feature agreement. Slight differences were detected between the two groups. Specifically, children with DLD experienced difficulties with the agreement on the feature [+telic] and that on the feature [+dynamic], while children with HFA-LI had difficulties with the agreement on the feature [+dynamic] and that on the feature [−dynamic]. This study supports the idea of a common symptomatology for the two disorders. More importantly, it suggests that these two disorders, DLD and HFA-LI, are not altogether the same in terms of language impairment. This paper concludes that general labels should not be simply attached to any children with language disorders. Instead, atypical language is very worthy of further analysis in the categorization of language disorders. [ABSTRACT FROM AUTHOR]

Autistic children, also known as "children from the stars", have been discovered for more than half a century, but there is still no unified conclusion on the diagnosis, causes, manifestations, and education of autism. The current theory and practice suggest that there is a need to improve the treatment and education of these children. According to existing theories and practices, most autistic children show a special interest in music, and music is very effective in the treatment of autistic children, and through musical activities, children with autism can improve their language, social and emotional, cognitive, and sensorimotor development. In this paper, we record and observe the music classes of children with autism. We select two classes with a total of seven children with autism as the observation subjects in the music classes, record the changes in various aspects and behavioral performance of these seven children with autism in the music activities, and analyze and summarize them. The main purpose of this study is to analyze and summarize how the three major music teaching methods are implemented in the music classroom for autistic children and how they can help autistic children with different characteristics. In the end, we summarize the main problems of music teaching for autistic children found in practice and try to make some suggestions, hoping to provide reference for scholars who study music education for autistic children. The music teaching activities were effective in improving the children's joint attention, movement imitation, rhythm imitation, and cooperation ability, and all three children improved to varying degrees, fulfilling the goals of the teaching activities. The behavioral analysis of the three children during the teaching activities showed that the three children improved their ability to sit comfortably, awareness, musical ability, and rule awareness and reduced inappropriate behaviors and bad emotions, which proved that music education could improve the social and cognitive skills of the children. [ABSTRACT FROM AUTHOR]

Robot treatments for children with autism have proven to be successful and effective. However, the resources needed for the treatments do not always meet the needs of the children. We overcame the lack of equipment and staff by extending the concept of robot therapy using a web and mobile application. This application enables greater availability and personification of the therapy itself. Its use in the majority of respondents contributes to improving their condition. This approach increases the flexibility of the therapy itself and makes it more accessible, enabling the patients to progress more rapidly. Although the robotic treatment presented in this paper is specific to children with autism, this approach can be generalized and applied to other areas where there are similar types of therapies. [ABSTRACT FROM AUTHOR]

Children with autism spectrum disorder (ASD) present unique characteristics that include a strong interest in objects or things. This strong interest is often viewed negatively as something that needs to be controlled or even targeted for elimination. In contrast, an affinity-based approach views these strong interests in a positive light--viewed as affinities, aptitudes, unique skills--that should not only be allowed but also encouraged. More importantly, the affinity-based approach employs the child's affinities to communicate and understand the child and to expand the child's repertoire of skills. This paper presents the affinity-based approach with application to promoting physical activity. Specific examples are presented that include using affinities to help children with ASD learn new skills such as using weight machines and cardio machines, practice and become more independent with an exercise routine, and ultimately enjoy and become a habitual exerciser. [ABSTRACT FROM AUTHOR]

Copyright of Forum Pedagogiczne / Pedagogical Forum is the property of Uniwersytet Kardynala Stefana Wyszynskiego w Warszawie and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Educational robotics (ER) is a growing interdisciplinary field that is attracting increasing attention in inclusive or special education settings. It provides a suitable educational environment for the participation of students with autism, through which they can utilize their main strengths and interests. Strengths-based vs. deficits-based approaches recognize the strengths and interests of autistic children as the starting point for their inclusion in school and the community. The scoping review was developed as the best knowledge-synthesis method for summarizing the pertinent research on the participation of students with autism in educational robotics for their successful inclusion. Forty-five studies were included and analyzed to address the main objectives, the mapping of contextual dimensions, and the specific characteristics of the educational robotic activities where the participation of students with autism occurred. The data were extracted into a charting framework, and a narrative analysis was adopted for the knowledge synthesis. According to the results, the research on the participation of children with autism is limited and has focused primarily on educational robotic activities, failing to adequately explore other dimensions that affect the successful participation and inclusion of students with autism in educational robotics. [ABSTRACT FROM AUTHOR]

Primary caregivers are the main mediators of care for children with an autism diagnosis in Canada, and the navigation process to gain access to autism-related services is known to be a major burden. These challenges to service access are compounded for newcomers to Canada, which include immigrants and refugees. The purpose of this scoping review is to describe the available research on Canadian newcomer caregiver experiences navigating and accessing autism-related services. After a systematic search and screening process, 28 studies were included. Data were extracted regarding the populations, study aims, and themes reported. Included studies characterized barriers and facilitators to service access and navigation specific to immigrants, while limited information was available for refugees. Based on the existing literature, the authors provide recommendations for possible research approaches, populations to include, and themes to examine in future research to promote health equity in Canadian autism service access. [ABSTRACT FROM AUTHOR]

Background: As countries like India improve access to maternal and infant care, the health systems need to develop services that enable all children to thrive. A key demographic which needs to be supported are children with disabilities, such as autism. With an estimated prevalence of one percent, there are over five million young children who need services to support their needs. However, the paucity of specialist care makes access to interventions diffcult. In this context a public health research not-for-profit is evaluating the effectiveness of the task-sharing approach to support the delivery of an evidenced social communication intervention for young children with autism. This paper describes the process of engaging and training the non-specialist frontline Accredited Social Health Activists (ASHAs), who are embedded within the Ministry of Health and Family Welfare under the Delhi State Health Mission, to deliver a complex intervention for autism to inform the future scalability of services for neurodevelopmental disorders. Methods: The present study describes the process which included (i) engagement meetings, (ii) recruitment, (iii) training, (iv) internship, and (v) competency evaluation. The shortlisted ASHAs received a 7-day classroom training followed by an internship period with practice cases. Finally, competency assessments, comprising of a test of knowledge and skills through role-plays, was administered. Results: Twenty three Primary Urban Health Centers across seven districts of Delhi were approached and 408 ASHAs were engaged in initial meetings. Telephonic screening with 127 ASHAs resulted in 72 ASHAs being selected for in-person interviews. Of the 45 ASHAs who attended, 33 were shortlisted for training and 18 completed it. Fifteen ASHAs entered the internship of which 7 ASHAs achieved competency. Discussion and conclusion: There was significant attrition along the pathway to having a competent non-specialist worker deliver a complex autism intervention. The lessons learnt from this process can inform the possibility of developing a cadre of disability specific frontline health workers who can deliver evidence-based interventions for neurodevelopmental disorders under supervision. [ABSTRACT FROM AUTHOR]

Socially assistive robots are widely deployed in interventions with children on the autism spectrum, exploiting the benefits of this technology in social behavior intervention plans, while reducing their autistic behavior. Furthermore, innovations in modern technologies such as machine learning enhance these robots with great capabilities. Since the results of this implementation are promising, their total cost makes them unaffordable for some organizations while the needs are growing progressively. In this paper, a low-cost robot for autism interventions is proposed, benefiting from the advantages of machine learning and low-cost hardware. The mechanical design of the robot and the development of machine learning models are presented. The robot was evaluated by a small group of educators for children with ASD. The results of various model implementations, together with the design evaluation of the robot, are encouraging and indicate that this technology would be advantageous for deployment in child–robot interaction scenarios. [ABSTRACT FROM AUTHOR]

In the context in which it was demonstrated that humanoid robots are efficient in helping children diagnosed with autism in exploring their affective state, this paper underlines and proves the efficiency of a previously developed machine learning-based mobile application called PandaSays, which was improved and integrated with an Alpha 1 Pro robot, and discusses performance evaluations using deep convolutional neural networks and residual neural networks. The model trained with MobileNet convolutional neural network had an accuracy of 56.25%, performing better than ResNet50 and VGG16. A strategy for commanding the Alpha 1 Pro robot without its native application was also established and a robot module was developed that includes the communication protocols with the application PandaSays. The output of the machine learning algorithm involved in PandaSays is sent to the humanoid robot to execute some actions as singing, dancing, and so on. Alpha 1 Pro has its own programming language—Blockly—and, in order to give the robot specific commands, Bluetooth programming is used, with the help of a Raspberry Pi. Therefore, the robot motions can be controlled based on the corresponding protocols. The tests have proved the robustness of the whole solution. [ABSTRACT FROM AUTHOR]

Data collection is an important component of evidence-based behavioral interventions for children with autism, but many one-to-one aides (i.e., behavioral support staff) do not systemically collect quantitative data that are necessary for best-practice client progress monitoring. Data collection of clients' behaviors often involves labor-intensive pen-and-paper practices. In addition, the solitary nature of one-to-one work limits opportunities for timely supervisor feedback, potentially reducing motivation to collect data. We incorporated principles from behavioral economics and user-centered design to develop a phone-based application, Footsteps, to address these challenges. We interviewed nine one-to-one aides working with children with autism and seven supervisors to ask for their app development ideas. We then developed the Footsteps app prototype and tested the prototype with 10 one-to-one aides and supervisors through three testing cycles. At each cycle, one-to-one aides rated app usability. Participants provided 76 discrete suggestions for improvement, including 29 new app features (e.g., behavior timer), 20 feature modifications (e.g., numeric type-in option for behavior frequency), four flow modifications (e.g., deleting a redundant form), and 23 out-of-scope suggestions. Of the participants that tested the app, 90% rated usability as good or excellent. Results support continuing to develop Footsteps and testing its impact in a clinical trial. [ABSTRACT FROM AUTHOR]

It is well-documented that autism can be reliably diagnosed by age two and that early signs emerge most often between 18 and 24 months. However, despite the increased awareness and focus on early diagnosis, the average age of diagnosis is over 4 years old; even later for Black children and those who are Medicaid-eligible. In this paper, we will propose a framework for accurate and accelerated autism diagnosis for children before age three. The proposed framework emphasizes a collaborative diagnostic process, which relies heavily on Birth to Three provider knowledge and expertise. Considerations for next steps are presented. This approach could increase access to diagnosis of young children soon after first signs of autism emerge. [ABSTRACT FROM AUTHOR]

In this paper, we introduce a deep learning model to classify children as either healthy or potentially having autism with 94.6% accuracy using Deep Learning. Patients with autism struggle with social skills, repetitive behaviors, and communication, both verbal and non-verbal. Although the disease is considered to be genetic, the highest rates of accurate diagnosis occur when the child is tested on behavioral characteristics and facial features. Patients have a common pattern of distinct facial deformities, allowing researchers to analyze only an image of the child to determine if the child has the disease. While there are other techniques and models used for facial analysis and autism classification on their own, our proposal bridges these two ideas allowing classification in a cheaper, more efficient method. Our deep learning model uses MobileNet and two dense layers to perform feature extraction and image classification. The model is trained and tested using 3,014 images, evenly split between children with autism and children without it; 90% of the data is used for training and 10% is used for testing. Based on our accuracy, we propose that the diagnosis of autism can be done effectively using only a picture. Additionally, there may be other diseases that are similarly diagnosable. [ABSTRACT FROM AUTHOR]

This paper is the corpus-based exploration of the nature of content words used by children with autism in a conversation. It aims to investigate what does the frequency of content words inform about the conceptualization of events and what differences can be seen in the conceptualization of children with severe and mild autism. The theory of embodiment is adopted to analyze the content words related to the conversations regarding birthday and school events. A spoken corpus of the conversation of thirteen children with autism was built for the investigation. The results show the tendency of these children to use nouns and adjectives as compared to verbs in their conversations. Moreover, children with severe autism gave less linguistics responses as compared to children with mild autism. Their distinct sensoryperceptual experiences seem to impact the use of the content words and their conceptualization. [ABSTRACT FROM AUTHOR]

Copyright of HUM: Journal of the Faculty of Arts at the University of Mostar is the property of University of Mostar, Faculty of Arts and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Autism is called "spectrum" disorder because there is a wide variation in the type and the severity of symptoms that people experience. India has a vast population, diverse cultures, and multiple languages, making it crucial to under- stand the unique challenges faced by individuals with autism spectrum disorder in the Indian context. This narrative review explores the current state of knowledge about autism spectrum disorder in the Indian context. Databases such as PubMed, Google Scholar, Sage journals, and other sources were searched with relevant terms for preparing this review. All published literature till January 2023 was studied and those which met the inclusion criteria were included. The resources included were original research articles, review articles, web pages, and book chapters addressing the purpose of the paper. Forty-eight such studies which met the inclusion criteria were included in the study. Results showed that the prevalence of autism varied across different studies in India. The study found advanced paternal age, fetal distress, gestational respiratory infections, labor complications, preterm birth, neonatal jaundice, delayed birth cry, birth asphyxia, late initiation of breastfeeding, neonatal seizures, use of maternal hormonal intervention, and consanguinity as some of the identified risk factors of autism spectrum disorder. Parents and families of children with autism have to go through a complex negative experience, both in the family and the community. This negative experience is further compounded by the lack of awareness and access to appropriate professional help and resources. It can be concluded that there is an urgent need for services that help parents cope with the stress of parenting a child with autism. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Computer Science & Technology (JCS&T) is the property of Journal of Computer Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Children with Foetal Alcohol Spectrum Disorders (FASD) and Autism Spectrum Disorders (ASD) experience significantly higher rates of sleep disturbances than their typically developing (TD) peers. Pre-sleep anxiety and waking emotional content is known to affect the content and frequency of nightmares, which can be distressing to children and caregivers. This is the first study to analyse nightmare frequency and content in FASD, and to assess its association with psychometric outcomes. Using online caregiver questionnaires, we assessed reports from 277 caregivers of children with ASD (n = 61), FASD (n = 112), and TD children (n = 104) using the Children's Sleep Habits Questionnaire (CSHQ), the Child Behaviour Checklist (CBCL), the Spence Children's Anxiety Scale (SCAS), and the Behaviour Rating Inventory for Executive Functioning (BRIEF). Within the ASD group, 40.3% of caregivers reported their children had nightmares. Within the FASD group, 73.62% of caregivers reported their children had nightmares, and within the TD group, 21.36% of caregivers reported their children had nightmares. Correlation analysis revealed significant associations between anxiety and nightmares, maladaptive behaviour and nightmares, and executive functioning and nightmares in the TD and FASD groups, but not ASD group. This paper adds to the emerging body of work supporting the need for sleep interventions as part of clinical practice with regard to children with ASD and FASD. As a relatively niche but important area of study, this warrants much needed further research. [ABSTRACT FROM AUTHOR]

That parents should love their children is generally considered self-evident. But what this love should entail is still a topic of discussion. In this paper, we demonstrate that there is currently a trend towards biologizing and even neurologizing parental love - that is, the claim that loving parental relationships are required for the brain development of the child - and that this trend has important repercussions for how we conceive of responsibility for children. Parental love, we will argue, is increasingly being conceptualized in reductionist biological and neurological terms. For example, parenting experts often stress the importance of loving parental relationships for the healthy brain development of the child. Moreover, this trend affects mothers and fathers differently. We will demonstrate this by, firstly, looking into the brain-based parenting discourse in general and secondly, by reviewing the discussion surrounding the diagnosis of autism in particular. We will use the arguments of Jan Macvarish regarding neuro-parenting to demonstrate that parental love is increasingly thought of in reductionist biological and neurological terms. Here, we will discuss three issues. Firstly, we will look at how the neuro-parenting discourse primarily focuses on mothers and their responsibilities. Secondly, we will show how the current discourse on parental love defers child-raising to the realm of individual rather than collective responsibility. Thirdly, we will analyse the discourse on the biological effects of love insofar as it suggests that parents have a duty to love, since their attachment and commitment are deemed biologically necessary for the child's healthy development. Later on, we use our own qualitative research on how clinicians and parents experience a child's autism diagnosis to further demonstrate the complex relationship between neuro-discourse and responsibility. When parents are confronted with a diagnosis of autism in their child, seeking the advice of experts in neurodevelopmental disorders is seen as the obvious path for developing their parental love. The neurodevelopmental diagnosis of autism has an exculpatory effect that might be necessary to safeguard parental love, as it relieves parents of some of the responsibility they feel for the child's challenging behavior. We will demonstrate that parents are considered to have a duty to know a child's neurological status and a responsibility to act upon this status. Finally, we will point out the relevance of gender for autism and neuro-parenting. We conclude that research into the biology of parental love is a worthwhile endeavor, but that such work requires a less simplistic view of biology than is currently the case. In the current climate regarding the parents' (and specifically mothers') duty to love their children in a particular way, we will make a case in this paper for liberating both mothers and fathers from fixed parental roles. We will conclude by arguing for more collective responsibility to lovingly raise children. [ABSTRACT FROM AUTHOR]

Affect recognition is currently an active research area for machine learning researchers. Researchers are paying more and more attention to the assessment and the classification of emotions in people with mental disorders in order to propose monitoring healthcare systems and then to better assist patients. In this paper, a supervised learning method to classify Autism Spectrum Disorder (ASD) and to evaluate affect levels among autistic children is proposed. The use of methodologies for clinical patient monitoring and management is the focus of our research. YouTube video frames acquired in unconstrained environments and conditions of autistic children demonstrating typical autistic behaviors, as well as images of neurotypical people are used to evaluate the performance of the proposed approach. This paper also proposes an extended version of a dataset, including the additional affect labels corresponding to the affect levels of autistic children. Finally, experiments using different models were conducted to determine which architecture performed best. These experiments have shown very promising results for continuous affect recognition of children with ASD. Results show also that using a model that has only been trained on neurotypical subjects does not perform as great when the subjects are ASD children. • A video-based approach for continuous affect recognition of children with Autism. • A new transformer-based deep learning model for affect recognition from images. • Arousal and Valence annotation of the SSBD dataset. • Data concerning neurotypical people are not relevant to studying autistic children. • Stimming behavior and face analysis can help in autism assessment. [ABSTRACT FROM AUTHOR]

Background: The prevalence of autism spectrum conditions (ASC) is 1% in developed countries, but little data are available from mainland China, Hong Kong and Taiwan. This study synthesizes evidence relating to the prevalence of ASC in these areas and assesses the effects of research methodology on prevalence estimates. Methods: Systematic literature searches were conducted in PubMed, Web of Knowledge, China Web of Knowledge and Weipu databases, as well as relevant papers published from 1987 to 2011, reporting prevalence estimates of ASC or childhood autism in mainland China, Hong Kong and Taiwan. Summary estimates of prevalence were calculated with a random effects model. The effects of research methodology on the prevalence estimates were assessed using a meta-regression model. Results: There were 25 studies eligible for review, 18 of which were suitable for inclusion in a meta-analysis. Pooled prevalence of childhood autism was 11.8 per 10,000 individuals (95% confidence interval (CI): 8.2, 15.3) in mainland China. Pooled prevalence of ASC was 26.6 per 10,000 (95% CI: 18.5, 34.6) in three areas. Substantial heterogeneity was identified between studies (I2>75%). The prevalence estimate of childhood autism was most strongly associated with the choice of screening instrument. After adjustment for age group, the odds ratio for prevalence estimates when using the Autism Behavior Checklist (ABC) as the screening instrument compared with those using the Clancy Autism Behavior Scale (CABS) was 0.29 (95% CI: 0.12, 0.69), and 1.79 (95% CI: 0.70, 4.55; P= 0.20) when using the Checklist for Autism in Toddlers (CHAT) compared to the CABS. Conclusions: The available studies investigating the prevalence of ASC in China, Hong Kong and Taiwan have focused mainly on childhood autism rather than the whole spectrum. The prevalence estimates are lower than estimates from developed countries. Studies using more recently developed screening instruments reported higher prevalence than older ones. However, available studies have methodological weaknesses and therefore these results lack comparability with those from developed countries. Our findings indicate a potential under-diagnosis and under-detection of ASC in mainland China, Hong Kong and Taiwan, and a need to adopt more advanced methods for research of ASC in these areas. [ABSTRACT FROM AUTHOR]

We explore whether staging (a combination of symbols, drawings, paintings, and re-creating action using Playmobil figures) used as a communicative activity of shared experiences influences the sense of fellowship. This study is part of a combined research and development project, and the findings are canalised back into the daily work. The assistants are interviewed, and the data are analysed in a coding process. We found that (1) 'being confident' is important for belongingness. Staging supports a shared understanding and a shared feeling of belonging. We also found that (2) developing a shared repertoire of concepts is possible when staging, and this scaffolds the fellowship. However, the concepts and the communication must (3) be meaningful to all parties. One does not take part in communication without meaning, and when one does not participate, one is not part of the fellowship. Staging enabled Magne, the main person in this study, to express himself better. Moreover, when discussing a shared experience with the personal assistants, Magne seemed to communicate well and showed signs of belonging. We conclude that communication about shared activities and experiences leads to interest and engagement and fosters a shared feeling of 'doing something together' and being part of a fellowship. [ABSTRACT FROM AUTHOR]

Children with autism spectrum disorder (ASD) often demonstrate deficits in motor skill performance, such as running, jumping, kicking, and physical fitness in comparison to children without ASD. The relationships between physical fitness and motor skills have been largely unexplored in children with ASD. This paper describes the implementation of a summer camp program that focused on physical activity and motor skill development for children with ASD; a secondary purpose was to assess motor skill performance, muscle strength and aerobic fitness correlations in children who have ASD. This study was conducted at a summer day camp for children with ASD. Participants completed a pre-screening process to determine appropriateness for the study. Measurements included wellness checks, motor skills testing, cardiorespiratory fitness, muscular strength, and gross motor skills. Cross sectional data were collected using "snapshot" data collection. Ten boys with ASD participated in the study. Overall, no significance was found regarding the correlation between gross motor skills and fitness levels of the participants. [ABSTRACT FROM AUTHOR]

It is important to engage children with ASD and the families that support them in research. However, it is often challenging for researchers to engage this population in time- and/or labor-intensive research due to the many barriers caregivers of children with ASD face. From a researcher's perspective, this challenge ultimately inhibits research designs and compromises the learning and understanding needed to identify meaningful research questions, solve relevant problems, and implement solutions into practice. One way researchers can support families with ASD to participate in research is through the building of academic-community partnerships. Academic-community partnerships can serve as both a solution to increasing participation in research and a complementary practice benefiting the child with ASD throughout the research process. Thus, the purpose of this paper is to describe how researchers might leverage academic-community partnerships to effectively engage children and families of children with ASD in research. [ABSTRACT FROM AUTHOR]