درخت حوزه‌های تخصصی

Background: Autism spectrum disorder is a neuro-developmental disorder with a significant deficiency in communication characteristics, social interactions and stereotyped behaviors. Aim: The purpose of this study was to investigate physical activity participation in Iranian children and adolescent with autism spectrum disorders. Materials and Methods: The research method was descriptive and survey. The statistical samples were 370 children and adolescent with ASD, age 8-20 years from Iran. The international physical activity questionnaire for older children and adolescents used for measuring physical activity levels. Data analyzed by using SPSS<sub>23 . Results: The results showed that 73.8% of participants were inactive during the last 7 days; 17.8% of them were active occasionally (1 to 2 times); 6.5% (3 to 4 times) and 1.1% (5 to 6 times) were physically active. During the last 7 days on weekends, 58.2% reported usually sitting position, 22.2% walking or standing, and 14.6% running or active playing and only 1.1% reported lots of running or playing. There was no significant difference in physical activity levels between girls and boys. Conclusion: The results showed the limited participation in physical activity among Iranian children and adolescents with ASD. This study seems to be a helpful for identifying the patterns and promotion of physical activity.

The main purpose of this study was to provide a framework of effective components in Iranian championship sports with a data mining approach. The research method was qualitative. The advanced search was performed in the general framework of factors affecting the sports industry and development and integration with data-driven technologies. Based on the literature review, 15 frameworks in the field of sports and 13 frameworks for the development and integration of the sports industry with technology were identified. After the data analysis, a researcher-developed framework for the championship sports industry for the use of data-driven technologies and data mining was presented in three parts. In the first part, nine influential factors including athletes/champion teams, leagues/clubs, stadiums/sports venues, fans/spectators, brands, media, government, academic/research institutions, and technology companies, were identified. In the second part, a strategic plan based on the development and integration of sports industry with data-driven technologies and data mining was presented, which includes four stages: Identifying and selecting talents, pre-game and match preparation, in-game and match activities, and post-match and match analysis. All data-driven activities and data mining in the first and second sections were performed by the IBM data science analysis methodology presented in the third section. Then, a conceptual framework was provided to 7 experts and their opinions were collected through semi-structured interviews and focus group methods. This conceptual framework enables sports managers to plan for their organization and adopt appropriate strategies using data-driven technologies and data mining.