Difficulties In Interaction Research Articles

On the Admission of Patients with Borderline Personality Disorder to Outpatient Psychotherapy

Patients with borderline personality disorder (BPD) present difficulties in self-regulation and interaction, which is a challenge for psychotherapists that is also addressed in BPD-specific interventions. Against this background, outpatient psychotherapists were surveyed about the factors playing a decisive role in their treatment offer for patients with BPD. Psychotherapists for adults were contacted via their email address published on the website of the Kassenärztliche Vereinigung (Association of Statutory Health Insurance Physicians), 231 of whom answered an online questionnaire. The results were analysed descriptively and examined inferentially with regard to the psychotherapists' admission behaviour. Almost 90% reported that they would generally accept patients with BPD in therapy. However, of those, 85% did not have a therapy slot available. The psychotherapists' learned approach of treatment was not a decisive factor in determining whether they were willing to provide treatment. Most of the psychotherapists (85%) recommended a BPD disorder-specific therapy such as Dialectical Behavior Therapy (DBT), Mentalization-Based Treatment (MBT), Transference-Focused Psychotherapy (TFP) or Schema Therapy (ST). However, only just under 7% were certified in such a disorder-specific approach. Significant individual stress factors described by the psychotherapists were suicidal risk (70%) and potential other-directed aggression (59%). In addition, it was shown that it played a role whether the psychotherapists were trained in an additional therapy approach (with at least 16 teaching units) or not. The care situation for people with BPD seeking an outpatient psychotherapy place is clearly in need of improvement. This is mainly due to a general lack of available therapy places as well as various fears and anxieties, such as increased suicidality, which in turn can have a negative impact on the provision of outpatient therapy. Psychotherapists who have undergone disorder-specific further training feel less burdened by suicidal behaviour. However, since only a small number of them are able to offer BPD-specific therapies, it is essential to expand and (financially) support specific training programmes. In order to meet the demand for care, professional changes are urgently needed.

Mitochondria in depression: The dysfunction of mitochondrial energy metabolism and quality control systems.

Depression is the most disabling neuropsychiatric disorder, causing difficulties in daily life activities and social interactions. The exact mechanisms of depression remain largely unclear. However, some studies have shown that mitochondrial dysfunction would play a crucial role in the occurrence and development of depression. To summarize the known knowledge about the role of mitochondrial dysfunction in the pathogenesis of depression. We review the recent literature， including 105 articles, to summarize the mitochondrial energy metabolism and quality control systems in the occurrence and development of depression. Some antidepressants which may exert their effects by improving mitochondrial function are also discussed. Impaired brain energy metabolism and (or) damaged mitochondrial quality control systems have been reported not only in depression patients but in animal models of depression. Although the classical antidepressants have not been specially designed to target mitochondria, the evidence suggests that many antidepressants may exert their effects by improving mitochondrial function. This brief review focuses on the findings that implicate mitochondrial dysfunction and the quality control systems as important etiological factors in the context of depressive disorders. It will help us to understand the various concepts of mitochondrial dysfunction in the pathogenesis of depression, and to explore novel and more targeted therapeutic approaches for depression.

How do children with language disorder perceive their peer interactions? A qualitative investigation.

Peer interaction difficulties are often elevated amongst children with language disorders, yet the mechanisms underlying these difficulties are unclear. Previous research indicates that poor conflict management, social withdrawal, emotion regulation difficulties, and reduced prosocial behavior may contribute to peer interaction difficulties. However, this research often uses adult perspectives, failing to acknowledge child perceptions of these experiences. The present study aimed to qualitatively investigate perceptions of peer interactions from the perspective of children with language disorders. Seven participants aged between 7- and 10-years-old took part. All participants were diagnosed with a language disorder and had language as their primary area of difficulty. Participants were recruited from a specialist language school and via an online database. Semi-structured interviews were conducted, with participants given the choice to answer questions verbally or creatively, using toys or drawing materials. Interview transcripts were analyzed using interpretative phenomenological analysis. Participants valued play, conversation, and helping others. They felt that spending time with peers could alleviate loneliness. However, sometimes solitude was needed as social interaction could be overwhelming. Participants found conflict challenging and exhibited difficulties with regulating emotions. Participants relied on running away, retaliation, or asking an adult for help, to resolve conflict. The findings suggest that children with language disorders are socially motivated and have relative strengths in displaying prosocial behavior. However, children with language disorders require support to promote positive relationships. This support includes help with making deeper connections with peers, opportunities to spend time alone when needed, and providing adept conflict resolution and emotion regulation strategies.

Is There a Bias Towards Males in the Diagnosis of Autism? A Systematic Review and Meta-Analysis.

Autism is more frequently diagnosed in males, with evidence suggesting that females are more likely to be misdiagnosed or underdiagnosed. Possibly, the male/female ratio imbalance relates to phenotypic and camouflaging differences between genders. Here, we performed a comprehensive approach to phenotypic and camouflaging research in autism addressed in two studies. First (Study 1 - Phenotypic Differences in Autism), we conducted a systematic review and meta-analysis of gender differences in autism phenotype. The electronic datasets Pubmed, Scopus, Web of Science, and PsychInfo were searched. We included 67 articles that compared females and males in autism core symptoms, and in cognitive, socioemotional, and behavioural phenotypes. Autistic males exhibited more severe symptoms and social interaction difficulties on standard clinical measures than females, who, in turn, exhibited more cognitive and behavioural difficulties. Considering the hypothesis of camouflaging possibly underlying these differences, we then conducted a meta-analysis of gender differences in camouflaging (Study 2 - Camouflaging Differences in Autism). The same datasets as the first study were searched. Ten studies were included. Females used more compensation and masking camouflage strategies than males. The results support the argument of a bias in clinical procedures towards males and the importance of considering a 'female autism phenotype'-potentially involving camouflaging-in the diagnostic process.

Descriptive Analysis of Social Interaction and Communication Skills of Autistic Children According to Sibling Status and Characteristics.

Sibling relationships in early childhood can have a positive impact on children's social interaction and communication skills. Similarly, autistic children can benefit from interactions with their siblings, who can serve as readily available partners for social interaction. However, there is a lack of research on the effects of siblings based on specific characteristics of the sibling. Therefore, the aim of this study is to compare social interactions and communication skills of autistic children based on sibling status and characteristics. We conducted a retrospective data review involving 895 autistic children and their siblings at Seoul National University Bundang Hospital. Variety of diagnostic assessments or questionnaires were administered. Based on the characteristics of the data, Quade's test for nonparametric analysis of covariance was used to compare autism-related symptoms and levels of functioning of the autistic child according to 1) sibling status, 2) birth order, 3) sex, and 4) diagnosis of the sibling. Pearson correlation was used to explore associations between the sibling age gap and different clinical scores. Having siblings was associated with fewer difficulties in restricted and repetitive behaviors. Based on the comparison of the Autism Diagnostic Interview-Revised scores, autistic children with multiple siblings demonstrated better nonverbal behaviors. Autistic children with autistic siblings experienced greater difficulties in social interactions and communications, such as peer relationships, sharing enjoyment, and engaging in social imitative play. The study revealed differences in social interactions and communication skills of autistic children based on sibling status, birth order, affected sibling, age gap, and sex.

The use of Arabic Language Sample Analysis as a screening tool in kindergarten Egyptian bilingual children

BackgroundLanguage sample analysis is a naturalistic method used for measuring child’s expressive language abilities. It is used in case of difficulty in direct interaction in remote places or pandemics.Aim of the workThe aim of this study is to evaluate the use of a language sample analysis as an easy applicable screening tool for narrative ability in kindergarten Egyptian bilingual children in order to reach a better understanding of their language profile. Subjects and methods: 150 bilingual Egyptian preschool male and female children exposed to Arabic and English languages were included and divided into two groups according to their age. All were subjected to the BEA-LSA narration assessment including macrostructure, microstructure items, and conversation assessment including verbal and nonverbal items.ResultsThe results revealed that bilingual children showed better performance in English than Arabic in most of the narration and conversation tasks. However, there was equal development between both age groups in English language regarding temporality, connectives, and reference clarity. The older age group showed higher code switching than younger age group and code switching occurred more from Arabic to English language. Both age groups bilingual children showed better frequency of words and mean length of utterance in narration. While in conversation, both age groups showed better type token ratio. Language sample analysis showed good test–retest reliability.ConclusionLanguage sample analysis could identify the characteristic profile of bilingual kindergarten Egyptian children and was a reliable method to analyze both narration and conversation skills of bilingual children.

Emotional Face Processing in Autism Spectrum Condition: A Study of Attentional Orienting and Inhibitory Control.

A core feature of Autistic Spectrum Condition (ASC) is the presence of difficulties in social interactions. This can be explained by an atypical attentional processing of social information: individuals with ASC may show problems with orienting attention to socially relevant stimuli and/or inhibiting their attentional responses to irrelevant ones. To shed light on this issue, we examined attentional orienting and inhibitory control to emotional stimuli (angry, happy, and neutral faces).An antisaccade task (with both prosaccade and antisacade blocks) was applied to a final sample of 29 children with ASC and 27 children with typical development (TD).Whereas children with ASC committed more antisaccade errors when seeing angry faces than happy or neutral ones, TD children committed more antisaccade errors when encountering happy faces than neutral faces. Furthermore, latencies in the prosaccade and antisaccade blocks were longer in children with ASC and they were associated with the severity of ASC symptoms. Thus, children with ASC showed an impaired inhibitory control when angry faces were presented.This bias to negative high-arousal information is congruent with affective information-processing theories on ASC, suggesting that threatening stimuli induce an overwhelming response in ASC. Therapeutic strategies where train the shift attention to emotional stimuli (i.e. faces) may improve ASC symptomatology and their socials functioning.

Knowledge and awareness of autism spectrum disorder among Libyans

Background: Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by the presence of delayed or defective development before the age of three years, as well as behavioral difficulties in social communication and interaction. Objective: To evaluate ASD knowledge and awareness, as well as ASD information sources in a sample of the Libyan general population, and to explore factors that could be associated with the knowledge and awareness. Methods: A cross-sectional study was carried out between 22 March and 13 August 2022 using a self-administered questionnaire. Results: Out of 2195 participants, 48.9% were females and 51.1% were males. Three-quarters of the participants (74.8%) presented a low level of knowledge. Of those whose source of knowledge of autism was social media, 78.9% had a low level of knowledge. However, 57.9% of the participants showed a good level of awareness of autism symptoms and signs. Conclusion: The participants had a limited understanding of the causes and characteristics of ASD. Raising community awareness of the causes and characteristics of ASD is a priority.

Managing Distance Learning for Secondary School Students in Tanzania during the COVID-19 Outbreak: Challenges and Opportunities Implicating Educational Inequality

This study explored the lived experiences of secondary school students in Moshi Municipality with distance learning amid the COVID-19 outbreak in Tanzania. Specifically, it explored the challenges and opportunities of learning amid the COVID-19 pandemic, and the roles assumed by parents and teachers to support secondary school students’ distance learning. A qualitative approach, framed within the phenomenography research design, guided the present study. Nineteen secondary school students were purposively selected from four secondary schools in Moshi Municipality. Data were collected through in-depth interviews and focus group discussions. The collected data underwent a systematic inductive content analysis to identify emerging themes from the data. The findings indicate that different approaches or methods were utilised by students for distance learning, including printed materials for self-study, TV and radio programmes, online resources, and online interactive classes. However, challenges such as limited internet access and limited device availability emerged as significant hurdles. Additionally, emotional struggles, including loneliness and motivational issues, were evident, while the absence of peer interaction and concentration difficulties were notable concerns. On the positive side, flexible learning environments allowed for self-paced learning, skill development, and the exploration of personal interests. Students capitalised on the autonomy of distance learning to discover new abilities and passions. The present study recommends that teachers continue to explore innovative teaching methods, like recorded audio lessons and supplementary resources to enhance students' learning experiences. The study suggests provisional of professional development opportunities to equip educators with the necessary skills for effective distance teaching.

How does a ‘Jewellery Club’ adaptation of the Lego Therapy intervention impact on social anxiety and interactions between girls aged 7 with social communication interaction difficulties?

AbstractThis study investigated the impact of a ‘Jewellery Club’ on girls with social, communication and interaction difficulties. The project focussed on three girls aged seven who participated in an intervention using similar principles to the ‘Lego Therapy’ intervention. An action research approach was followed, where two phases of the intervention were undertaken with participants engaging with a weekly 20 min session for 3 weeks per phase. The impact of the intervention was assessed through the use of a social difficulties log, field notes and unstructured interviews with parents. Findings identified an overall reduction in social difficulties and social anxiety related to school as well as improved play experiences for the participants during unstructured school times and highlighted the importance of the intervention being aligned with the interests of the participants. The findings suggest that reflection on the gendered nature of interventions may be useful when considering how research might be implemented in practice.

Autism spectrum disorder detection using facial images: A performance comparison of pretrained convolutional neural networks.

Autism spectrum disorder (ASD) is a complex psychological syndrome characterized by persistent difficulties in social interaction, restricted behaviours, speech, and nonverbal communication. The impacts of this disorder and the severity of symptoms vary from person to person. In most cases, symptoms of ASD appear at the age of 2 to 5 and continue throughout adolescence and into adulthood. While this disorder cannot be cured completely, studies have shown that early detection of this syndrome can assist in maintaining the behavioural and psychological development of children. Experts are currently studying various machine learning methods, particularly convolutional neural networks, to expedite the screening process. Convolutional neural networks are considered promising frameworks for the diagnosis of ASD. This study employs different pre-trained convolutional neural networks such as ResNet34, ResNet50, AlexNet, MobileNetV2, VGG16, and VGG19 to diagnose ASD and compared their performance. Transfer learning was applied to every model included in the study to achieve higher results than the initial models. The proposed ResNet50 model achieved the highest accuracy, 92%, compared to other transfer learning models. The proposed method also outperformed the state-of-the-art models in terms of accuracy and computational cost.

Real-time facial emotion recognition model based on kernel autoencoder and convolutional neural network for autism children

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder that is characterized by abnormalities in the brain, leading to difficulties in social interaction and communication, as well as learning and attention. Early diagnosis of ASD is challenging as it mainly relies on detecting abnormalities in brain function, which may not be evident in the early stages of the disorder. Facial expression analysis has shown promise as an alternative and efficient solution for early diagnosis of ASD, as children with ASD often exhibit distinctive patterns that differentiate them from typically developing children. Assistive technology has emerged as a crucial tool in improving the quality of life for individuals with ASD. In this study, we developed a real-time emotion identification system to detect the emotions of autistic children in case of pain or anger. The emotion recognition system consists of three stages: face identification, facial feature extraction, and feature categorization. The proposed system can detect six facial emotions: anger, fear, joy, natural, sadness, and surprise. To achieve high-performance accuracy in classifying the input image efficiently, we proposed a deep convolutional neural network (DCNN) architecture for facial expression recognition. An autoencoder was used for feature extraction and feature selection, and a pre-trained model (ResNet, MobileNet, and Xception) was applied due to the size of the dataset. The Xception model achieved the highest performance, with an accuracy of 0.9523%, sensitivity of 0.932, specificity of 0.9421, and AUC of 0.9134%. The proposed emotion detection framework leverages fog and IoT technologies to reduce latency for real-time detection with fast response and location awareness. Using fog computing is particularly useful when dealing with big data. Our study demonstrates the potential of using facial expression analysis and deep learning algorithms for real-time emotion recognition in autistic children, providing medical experts and families with a valuable tool for improving the quality of life for individuals with ASD.

Understanding Automation Failure

The implementation of automation in many domains has led to well-documented accidents and incidents, resulting from reduced situation awareness that occurs when operators are out-of-loop (OOTL), automation confusion, and automation interaction difficulties. Wickens coined the term lumberjack effect to summarize the finding that while automation works well most of the time in typical or normal situations, the performance problems that occur in novel or unexpected situations also increase the likelihood of catastrophic errors. Skraaning and Jamieson have criticized the lumberjack effect due to a study in which they failed to find it. I show that this claim is unsupported due to a number of methodological limitations in their study and conceptual errors. They also provide a model of automation failure that fails to clearly delineate the many barriers to accidents that are available, instead emphasizing the ways in which automation can fail technically and different types of human error. An alternate automation failure model is presented that provides a broader socio-technical perspective emphasizing the design features, processes, capabilities, organizational policies, and training that support people in improving system safety when automation fails.

Causes, Symptoms and Treatments for Autism: Literature Review

In the past few years, there has been critical advance in understanding the causes, symptoms, and medications for autism spectrum disorder (ASD). This literature review aims to summarize the current understanding of autism spectrum disorder (ASD) by examining various studies and research conducted in recent years. This review will focus on the causes, effects, different symptoms, and solutions for individuals that suffer from autism spectrum disorder (ASD). The patients often experience a wide range of effects that impact their social communication, behavior, and sensory processing. Difficulties in social interaction, communication challenges, repetitive behaviors, and sensory sensitivities are common characteristics of ASD. These effects can vary in severity and manifestation from person to person, highlighting the heterogeneous nature of the disorder.Genetic factors play a significant part, with certain gene mutations and varieties contributing to the development of ASD. Moreover, natural components and pre-birth complications are also related with higher risks of ASD.The paper discusses the implications of these findings in refining our understanding of autism and ultimately developing improved interventions and support mechanisms for individuals with autism spectrum disorder.

Mining Semantic Correlations Between Mispredictions and Corrections for Interactive Semantic Segmentation.

Interactive semantic segmentation pursues high-quality segmentation results at the cost of a small number of user clicks. It is attracting more and more research attention for its convenience in labeling semantic pixel-level data. Existing interactive segmentation methods often pursue higher interaction efficiency by mining the latent information of user clicks or exploring efficient interaction manners. However, these works neglect to explicitly exploit the semantic correlations between user corrections and model mispredictions, thus suffering from two flaws. First, similar prediction errors frequently occur in actual use, causing users to repeatedly correct them. Second, the interaction difficulty of different semantic classes varies across images, but existing models use monotonic parameters for all images which lack semantic pertinence. Therefore, in this article, we explore the semantic correlations existing in corrections and mispredictions by proposing a simple yet effective online learning solution to the above problems, named correction-misprediction correlation mining ( CM2 ). Specifically, we leverage the correction-misprediction similarities to design a confusion memory module (CMM) for automatic correction when similar prediction errors reappear. Furthermore, we measure the semantic interaction difficulty by counting the correction-misprediction pairs and design a challenge adaptive convolutional layer (CACL), which can adaptively switch different parameters according to interaction difficulties to better segment the challenging classes. Our method requires no extra training besides the online learning process and can effectively improve interaction efficiency. Our proposed CM2 achieves state-of-the-art results on three public semantic segmentation benchmarks.

Genetic underpinnings of the sex bias in autism spectrum disorder

Autism spectrum disorder (ASD) is a neurodevelopment condition featuring difficulties in social interaction and communication. ASD is also well-known for its sex bias, in which males are diagnosed approximately four times more frequently than females. Although recent sequencing studies have identified a genetic etiology of ASD, the sex bias in ASD still remains largely unexplained because the frequencies of autosomal ASD-associated genetic variations are equivalent between males and females. We hypothesized that if the intrinsic expression levels of ASD-associated genes are different between males and females, they may contribute to the sex bias in ASD. Aiming to decode the genetic contribution to the ASD sex bias, we determined whether gene expression levels of ASD-associated genes were different between undiagnosed males and females. Analyses of the ribonucleic acid sequencing (RNAseq) data from the Genotype-Tissue Expression consortium (GTEx) revealed modest differences for 17 ASD-associated genes in the relevant brain regions between males and females. These candidate genes showed stronger collective sex-dependent expression in the gene set enrichment analysis, which was subsequently validated by the RNAseq data from the PsychENCODE consortium. In addition, gene ontology analysis revealed the functional relevance of the 17 candidate genes in chromatin remodeling and synaptic regulation. Taken together, these candidate genes discovered through big data analysis suggest that sex-dependent expression of ASD-associated genes may contribute to the sex bias in ASD. These novel insights into the sex bias may refine underlying disease mechanisms of ASD, potentially informing therapeutic strategies for improving the quality of life of diagnosed individuals.

Assessing Psychological Implications in Children with Delayed Verbal Communication and Vocabulary Development: A Systematic Review

Background: Delayed verbal communication and vocabulary development can significantly impact children's emotional well-being, social interactions, and overall psychological development. This systematic review aims to synthesize existing research on the psychological effects associated with these delays, focusing on how they affect children's emotional health, social skills, and cognitive functioning. Methodology: This review systematically analyzed studies that investigated the psychological consequences of delayed verbal communication and vocabulary development in children. The studies included were diverse in design, including cross-sectional, longitudinal, and mixed-method approaches. Key measures across studies included assessments of depressive and anxiety symptoms, social-emotional functioning, language skills, and cognitive abilities. The analysis synthesized findings from a range of populations, including children with developmental language disorders (DLD), specific language impairment (SLI), and autistic spectrum disorders (ASD). Results: The review found that children with delayed verbal communication and vocabulary development are at increased risk for a variety of psychological issues. These include higher levels of anxiety and depression, difficulties in social interactions, and cognitive challenges. Specifically, children with DLD and SLI were more likely to experience emotional difficulties, such as depressive symptoms and anxiety, compared to their peers. Pragmatic language difficulties were found to be particularly associated with later psychotic experiences and depressive symptoms. Peer problems, bullying, and socioemotional challenges were prominent among youth with language impairments. Additionally, deficits in higher-order language skills and cognitive abilities were linked to greater emotional and social difficulties. Conclusion: The psychological impacts of delayed verbal communication and vocabulary development are profound, affecting children's emotional well-being, social interactions, and cognitive development. Interventions should address both language difficulties and associated emotional and social challenges.

Dual Kernel Support Vector-based Crossover Red Fox Algorithm: Advancements in Assistive Technology for Hearing-impaired Individuals

Individuals with hearing impairment face several challenges, including difficulties in communication, social interactions, and accessibility to information on various auditory abilities. Innovations range from hearing aids to advanced communication devices and mobile apps. Designing solutions that prioritize user feedback ensures a more inclusive and empowering experience for people with hearing impairment. Assistive technology (AT) endeavors to enhance the daily lives of individuals, fostering greater connectivity, and also plays a crucial role in addressing these challenges. Therefore, an attention dual kernel support vector-based crossover red fox (ADKS-CRF) algorithm is developed for superior performance. This research study proposes a model combining a dual kernel support vector machine with an attention mechanism to implicitly operate in a high-dimensional feature space without computing the transformed vector features. The crossover strategy is incorporated with the red fox optimization algorithm, and the integrated formation of CRF fine-tunes the parameters of the ADKS model, removing the complexity of local optima. This work conducted experiments using raw data from an effective 3D ear acquisition system dataset. Experimental validation is conducted using various evaluation measures to assess effectiveness. The proposed hybrid approach achieves a sensitivity of 97.8%, an F1-score of 97.1%, a specificity of 96.3%, an accuracy of 98.4%, a false alarm rate of 90.8%, and a Matthews correlation coefficient of 97.3%. The comparative analysis evaluates the efficacy of the ADKS-CRF method with various baseline approaches for the development of ATs for hearing-impaired people.

Research and Application of Virtual Reality Technology Based on the Medical Field of Autism

With the rapid advancement of technology, virtual reality has revolutionized various industries, including healthcare. In particular, the treatment of autism has greatly benefited from the integration of virtual reality technology. This study aims to provide an analysis and summary of the recent advancements and applications of virtual reality in the medical field for autism, based on a comprehensive literature review. It investigates how virtual reality technology is currently helping individuals with autism to alleviate the difficulties caused by complex symptoms, and explores effective treatment and rehabilitation approaches for different types of autism spectrum disorder. The study also examines specific autism disorders, such as social interaction difficulties and emotional regulation challenges. Furthermore, it outlines the numerous challenges that virtual reality technology faces in its development for medical applications in the field of autism. Finally, the paper concludes and offers future prospects in this domain.

Knowledge and awareness of autism spectrum disorder among Libyans.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by the presence of delayed or defective development before the age of three years, as well as behavioral difficulties in social communication and interaction. To evaluate ASD knowledge and awareness, as well as ASD information sources in a sample of the Libyan general population, and to explore factors that could be associated with the knowledge and awareness. A cross-sectional study was carried out between 22 March and 13 August, 2022 using a self-administered questionnaire. The study included 2350 individual aged 18 and up from households living in different regions in Libya (eastern, southern, central, and western). Out of 2195 participants, 48.9% were females and 51.1% were males. Three-quarters of the participants (74.8%) presented a low level of knowledge about autism causes. Of those whose source of knowledge of autism was social media, 78.9% had a low level of knowledge. However, 57.9% of the participants showed a good level of awareness of autism symptoms and signs. The participants had a limited understanding of the causes and characteristics of ASD. Raising community awareness of the causes and characteristics of ASD is a priority.