Background: Increased parental stress is strongly related to the severity of autism spectrum disorder (ASD) symptomatology. Parents’ coping strategies and social support issues add to the complexity of this relationship. Aim: The present study investigated the relationship between self-regulation skills and parenting stress in parents of nonverbal children with ASD. Methods and procedure: The Parenting Stress Index–Short Form (PSI-SF) was administered to 75 families, and self-regulation scores on a Motor Behavior Checklist for children (MBC) were recorded by students’ class teachers (level of functioning-behavioral problems). In addition, interviews were conducted with a focus group of six parents (four mothers and two fathers) to explore the underline factors of parental stressin-depth. Results: Correlation analyses revealed that parenting stress was positively correlated with elevated scores on MBC children’s self-regulation subscale. On the other hand, parenting stress was negatively correlated with the level of social functional support reported. Qualitative data were analyzed using transcripts, revealing additional stressors for families and parents, and resulting in recommendations to overcome these factors. Conclusions and implications: Aiming at developing strategies to improve self-regulation skills in nonverbal children with ASD may be particularly important in reducing parental stress for families having nonverbal children with autism and other developmental disabilities. Parents’ stressors and suggestions during interviews are also discussed.

This study aimed to explore school factors that influence students’ achievements in Trends in International Mathematics and Science Study (TIMSS) in schools in the Emirate of Abu Dhabi, in the United Arab Emirates. The study sample for TIMSS 2015 consisted of 4838 students in eighth grade; 2172 girls, 2666 boys, and 156 schools from Abu Dhabi attended and participated in TIMSS 2015. Principal component analysis (PCA) was run on 77 items of school questionnaires administered to school principals to provide information about the school contexts for teaching and learning. The five factors from the school questionnaire were general school resources, school discipline and safety, parental support, principal experience and education, and library and instruction resources. Multiple regression models were implemented to examine the impact of school factors on student achievement in TIMSS 2015. The models are statistically significant, indicating that they fit the data well. This also demonstrates a significant linear relationship between students’ achievement in TIMSS 2015 and the variables related to school factors.

Children’s emotional, behavioral, and developmental problems can be properly identified and assessed based on observations from their teachers and parents. The Motor Behavior Checklist (MBC) was designed to assist classroom teachers and Physical Education (PE) teachers in assessing their students’ motor-related behaviors. The instrument has already been successfully translated and culturally adapted into six languages and used in a number of research studies internationally. The present study aimed to develop the Arabic version of the MBC checklist and proceed with the necessary cross-cultural adaptations for the use of the instrument in Arabic speaking countries and especially in United Arab Emirates (UAE) primary schools. The translation and cultural adaptation of the MBC was based on the ten-step process: forward translation of the original instrument; development of a synthesized version, back-translation; linguistic and semantic comparisons; back translators evaluation of divergent items; development of a synthesized version; based on the back translators’ suggestions; clarity assessment of the synthesized version by professionals (teachers); additional assessment of clarity indicators by a focus group of experts; and development of the final version. Results indicated a satisfactory level of agreement between the original and the back-translated versions, while nine items required minor adjustments and two items needed major adaptations and word replacements to clarify their content and be fully adapted into the UAE culture. In the pilot use, UAE teachers confirmed the clarity of the items in an 84% percentage. The final translated version’s overall content was found sufficiently compatible with the original version of the instrument. The study highlights the importance of a rigorous translation process and the process of cultural adaptation.

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition with rising global prevalence, driven by improved awareness and diagnostic practices. Early diagnosis and intervention are crucial for better outcomes, yet delays persist due to systemic inefficiencies and sociocultural disparities. Artificial Intelligence (AI), including machine learning (ML) and deep learning (DL), offers promising tools for accurate and efficient ASD detection, reducing diagnostic delays and human error. AI-driven tools like Canvas Dx and EarliPoint System show high accuracy, while hybrid models and explainable AI (XAI) enhance precision and interpretability. However, ethical concerns and equitable access remain challenges. AI integration can improve early diagnosis, personalized care, and long-term outcomes for individuals with ASD.