5 research outputs found
βAut Fitnessβ β a Technology for Organizing Classes on Adaptive Physical Education for Children with ASD
The motor sphere in children with ASD is frequently affected in association with low social and communicative skills. This makes development of individually tailored physical education programs especially important. We present the results of contemporary foreign studies of the motor abilities of children with ASD that point to the efficiency of adaptive physical activities for motor development as well as acquiring everyday social and communicative skills. We present the first part of adaptive physical education technology “Aut Fitness”. The technology is based on the principles of organization of motions by N.A. Bernstein, the concepts of sensory integration and sensori-motor correction. The technology provides a comprehensive curriculum for physical ability and motor skills development of a child with ASD, from the diagnostic assessment to conceptualization of a training route to be implemented in close collaboration with the parents. The theoretical and methodological support is provided together with the aims of the technology for formation of motor skill and correction of behavior typical for ASD. The specifics of motor activity disorders in children with ASD and additional factors that make it difficult to study in physical education classes are described. Targets in the areas of general development, adaptation, health, well-being and age-specific advancement are identified and described. These are the development of strength, dexterity, endurance, coordination abilities; training in breathing exercises and elements of sports games; prevention and correction of posture disorders. The stages of the implementation of programs developed using the “Aut Fitness” technology are described These are a system of classes aimed at the harmonious motor and communicative development of children with ASD, taking into account their level of physical fitness.</p
Π₯Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊΠ° ΡΠΏΠΈΠ΄Π΅ΠΌΠΈΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΎΠΉ ΡΠΈΡΡΠ°ΡΠΈΠΈ ΠΏΠΎ COVID-19 Π² Π ΠΎΡΡΠΈΠΉΡΠΊΠΎΠΉ Π€Π΅Π΄Π΅ΡΠ°ΡΠΈΠΈ Π² 2020 Π³.
Background.The COVID-19 epidemic in the Russian Federation, which began in March 2020, caused serious damage to health of the population and led to severe economic losses. By December 28, 2020, 3 078 035 cases of COVID-19 and 55 265 lethal outcomes were registered in the country. The population of all territorial subjects of the country is involved in the epidemic process of COVID-19. The severe epidemiological situation made it necessary to conduct an analysis to identify the factors that determine the high intensity of the epidemic process, as well as the population groups with the highest risk of SARS-CoV-2 infection.
Aims to study the patterns of SARS-CoV-2 spread and the epidemiological features of the initial stage of the COVID-19 pandemic in the Russian Federation in 2020.
Methods.An epidemiological analysis of the COVID-19 situation in the Russian Federation was carried out to determine the dynamics of morbidity, the gender proportion and age structure of patients, the proportion of hospitalized patients, the ratio of various forms of infection, the social and professional status of patients. Standard methods of descriptive statistics Microsoft Excel and STATISTICA 12.0 (StatSoft, USA) were used for statistical processing. The mean values were estimated with a 95% confidence interval [95% CI] (the exact Klopper Pearson method).
Results.During the observation time (2020), several periods were identified in the dynamics of the new COVID-19 cases detection: the period of importation of SARS-CoV-2 and the increase in morbidity, the period of epidemic decline, the period of autumn growth, the period of sustained high incidence of COVID-19. It was found that people over 70 years of age are the group with the highest risk of infection and a more severe course of COVID-19. The presence of target contingents among social and professional groups of the population, which should include medical workers, retired person, employees of educational institutions, law enforcement agencies, transport, who require special attention and medical and social support, was shown.
Conclusions.The analysis showed that the large-scale spread of COVID-19 requires in-depth epidemiological studies and the development of additional disease control measures, taking into account the dynamics of the incidence of this socially significant infection.ΠΠ±ΠΎΡΠ½ΠΎΠ²Π°Π½ΠΈΠ΅.ΠΠΏΠΈΠ΄Π΅ΠΌΠΈΡCOVID-19Π²Π ΠΎΡΡΠΈΠΉΡΠΊΠΎΠΉ Π€Π΅Π΄Π΅ΡΠ°ΡΠΈΠΈ, Π½Π°ΡΠ°Π²ΡΠΈΡΡΠ²ΠΌΠ°ΡΡΠ΅ 2020 Π³., Π½Π°Π½Π΅ΡΠ»Π° ΡΠ΅ΡΡΠ΅Π·Π½Π΅ΠΉΡΠΈΠΉ ΡΡΠ΅ΡΠ± Π·Π΄ΠΎΡΠΎΠ²ΡΡ Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡΠΈΠΏΡΠΈΠ²Π΅Π»Π°ΠΊΡΡΠΆΠ΅Π»ΡΠΌ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΈΠΌ ΠΏΠΎΡΠ΅ΡΡΠΌ.Π28 Π΄Π΅ΠΊΠ°Π±ΡΡ 2020 Π³.Π²ΡΡΡΠ°Π½Π΅ Π·Π°ΡΠ΅Π³ΠΈΡΡΡΠΈΡΠΎΠ²Π°Π½ΠΎ 3 078 035 ΡΠ»ΡΡΠ°ΡCOVID-19ΠΈ55 265 Π»Π΅ΡΠ°Π»ΡΠ½ΡΡ
ΠΈΡΡ
ΠΎΠ΄ΠΎΠ².ΠΡΠΏΠΈΠ΄Π΅ΠΌΠΈΡΠ΅ΡΠΊΠΈΠΉ ΠΏΡΠΎΡΠ΅ΡΡCOVID-19 Π²ΠΎΠ²Π»Π΅ΡΠ΅Π½ΠΎ Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΠ΅ Π²ΡΠ΅Ρ
ΡΡΠ±ΡΠ΅ΠΊΡΠΎΠ² Π ΠΎΡΡΠΈΠΉΡΠΊΠΎΠΉ Π€Π΅Π΄Π΅ΡΠ°ΡΠΈΠΈ. Π’ΡΠΆΠ΅Π»Π°Ρ ΡΠΏΠΈΠ΄Π΅ΠΌΠΈΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠ°Ρ ΡΠΈΡΡΠ°ΡΠΈΡΠ²ΡΡΡΠ°Π½Π΅ ΠΎΠ±ΡΡΠ»ΠΎΠ²ΠΈΠ»Π° Π½Π΅ΠΎΠ±Ρ
ΠΎΠ΄ΠΈΠΌΠΎΡΡΡ ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½ΠΈΡ Π°Π½Π°Π»ΠΈΠ·Π°ΡΠ²ΡΡΠ²Π»Π΅Π½ΠΈΠ΅ΠΌ ΡΠ°ΠΊΡΠΎΡΠΎΠ², ΠΎΠΏΡΠ΅Π΄Π΅Π»ΡΡΡΠΈΡ
Π²ΡΡΠΎΠΊΡΡ ΠΈΠ½ΡΠ΅Π½ΡΠΈΠ²Π½ΠΎΡΡΡ ΡΠΏΠΈΠ΄Π΅ΠΌΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΏΡΠΎΡΠ΅ΡΡΠ°,Π°ΡΠ°ΠΊΠΆΠ΅ Π³ΡΡΠΏΠΏ Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡΡΠ½Π°ΠΈΠ±ΠΎΠ»Π΅Π΅ Π²ΡΡΠΎΠΊΠΈΠΌ ΡΠΈΡΠΊΠΎΠΌ ΠΈΠ½ΡΠΈΡΠΈΡΠΎΠ²Π°Π½ΠΈΡSARS-CoV-2.
Π¦Π΅Π»Ρ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΠΈΠ·ΡΡΠΈΡΡ Π·Π°ΠΊΠΎΠ½ΠΎΠΌΠ΅ΡΠ½ΠΎΡΡΠΈ ΡΠ°ΡΠΏΡΠΎΡΡΡΠ°Π½Π΅Π½ΠΈΡSARS-CoV-2ΠΈΡΠΏΠΈΠ΄Π΅ΠΌΠΈΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΠΎΡΠΎΠ±Π΅Π½Π½ΠΎΡΡΠΈ Π½Π°ΡΠ°Π»ΡΠ½ΠΎΠ³ΠΎ ΡΡΠ°ΠΏΠ° ΠΏΠ°Π½Π΄Π΅ΠΌΠΈΠΈCOVID-19Π²Π ΠΎΡΡΠΈΠΉΡΠΊΠΎΠΉ Π€Π΅Π΄Π΅ΡΠ°ΡΠΈΠΈΠ²2020 Π³.
ΠΠ΅ΡΠΎΠ΄Ρ.ΠΡΠΎΠ²Π΅Π΄Π΅Π½ ΡΠΏΠΈΠ΄Π΅ΠΌΠΈΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΠΉ Π°Π½Π°Π»ΠΈΠ· ΡΠΈΡΡΠ°ΡΠΈΠΈΠΏΠΎCOVID-19Π²Π ΠΎΡΡΠΈΠΉΡΠΊΠΎΠΉ Π€Π΅Π΄Π΅ΡΠ°ΡΠΈΠΈΡΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΠ΅ΠΌ Π΄ΠΈΠ½Π°ΠΌΠΈΠΊΠΈ Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π΅ΠΌΠΎΡΡΠΈ, Π³Π΅Π½Π΄Π΅ΡΠ½ΠΎΠΉ ΠΏΡΠΎΠΏΠΎΡΡΠΈΠΈΠΈΠ²ΠΎΠ·ΡΠ°ΡΡΠ½ΠΎΠΉ ΡΡΡΡΠΊΡΡΡΡ Π·Π°Π±ΠΎΠ»Π΅Π²ΡΠΈΡ
, ΡΠ΄Π΅Π»ΡΠ½ΠΎΠ³ΠΎ Π²Π΅ΡΠ° Π³ΠΎΡΠΏΠΈΡΠ°Π»ΠΈΠ·ΠΈΡΠΎΠ²Π°Π½Π½ΡΡ
ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ², ΡΠΎΠΎΡΠ½ΠΎΡΠ΅Π½ΠΈΡ ΡΠ°Π·Π»ΠΈΡΠ½ΡΡ
ΡΠΎΡΠΌ ΠΈΠ½ΡΠ΅ΠΊΡΠΈΠΈ, ΡΠΎΡΠΈΠ°Π»ΡΠ½ΠΎΠ³ΠΎΠΈΠΏΡΠΎΡΠ΅ΡΡΠΈΠΎΠ½Π°Π»ΡΠ½ΠΎΠ³ΠΎ ΡΡΠ°ΡΡΡΠ° Π·Π°Π±ΠΎΠ»Π΅Π²ΡΠΈΡ
.ΠΠ»ΡΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΎΠ±ΡΠ°Π±ΠΎΡΠΊΠΈ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½Ρ ΡΡΠ°Π½Π΄Π°ΡΡΠ½ΡΠ΅ ΠΌΠ΅ΡΠΎΠ΄Ρ ΠΎΠΏΠΈΡΠ°ΡΠ΅Π»ΡΠ½ΠΎΠΉ ΡΡΠ°ΡΠΈΡΡΠΈΠΊΠΈ Microsoft ExcelΠΈSTATISTICA 12.0 (StatSoft, Π‘Π¨Π). Π‘ΡΠ΅Π΄Π½ΠΈΠ΅ Π·Π½Π°ΡΠ΅Π½ΠΈΡ ΠΎΡΠ΅Π½ΠΈΠ²Π°Π»ΠΈΡΡΡΠ΅ΡΠΎΠΌ 95% Π΄ΠΎΠ²Π΅ΡΠΈΡΠ΅Π»ΡΠ½ΠΎΠ³ΠΎ ΠΈΠ½ΡΠ΅ΡΠ²Π°Π»Π° [95% ΠΠ] (ΠΏΠΎ ΡΠΎΡΠ½ΠΎΠΌΡ ΠΌΠ΅ΡΠΎΠ΄Ρ ΠΠ»ΠΎΠΏΠΏΠ΅ΡΠ°ΠΠΈΡΡΠΎΠ½Π°).
Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ.ΠΠ°Π²ΡΠ΅ΠΌΡ Π½Π°Π±Π»ΡΠ΄Π΅Π½ΠΈΡ (2020 Π³.) Π²ΡΠ΄Π΅Π»Π΅Π½ΠΎ Π½Π΅ΡΠΊΠΎΠ»ΡΠΊΠΎ ΠΏΠ΅ΡΠΈΠΎΠ΄ΠΎΠ²Π²Π΄ΠΈΠ½Π°ΠΌΠΈΠΊΠ΅ Π²ΡΡΠ²Π»Π΅Π½ΠΈΡ Π½ΠΎΠ²ΡΡ
ΡΠ»ΡΡΠ°Π΅Π²COVID-19: ΠΏΠ΅ΡΠΈΠΎΠ΄ Π·Π°Π²ΠΎΠ·Π°SARS-CoV-2ΠΈΡΠΎΡΡΠ° Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π΅ΠΌΠΎΡΡΠΈ, ΠΏΠ΅ΡΠΈΠΎΠ΄ ΡΠΏΠΈΠ΄Π΅ΠΌΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π·Π°ΡΠΈΡΡΡ, ΠΏΠ΅ΡΠΈΠΎΠ΄ ΠΎΡΠ΅Π½Π½Π΅Π³ΠΎ ΠΏΠΎΠ΄ΡΠ΅ΠΌΠ°, ΠΏΠ΅ΡΠΈΠΎΠ΄ ΡΡΡΠΎΠΉΡΠΈΠ²ΠΎ Π²ΡΡΠΎΠΊΠΎΠ³ΠΎ ΡΡΠΎΠ²Π½Ρ Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π΅ΠΌΠΎΡΡΠΈCOVID-19. Π£ΡΡΠ°Π½ΠΎΠ²Π»Π΅Π½ΠΎ,ΡΡΠΎΠ»ΠΈΡΠ° ΡΡΠ°ΡΡΠ΅ 70 Π»Π΅Ρ ΡΠ²Π»ΡΡΡΡΡ Π³ΡΡΠΏΠΏΠΎΠΉΡΠ½Π°ΠΈΠ±ΠΎΠ»Π΅Π΅ Π²ΡΡΠΎΠΊΠΈΠΌ ΡΠΈΡΠΊΠΎΠΌ Π·Π°ΡΠ°ΠΆΠ΅Π½ΠΈΡΠΈΠ±ΠΎΠ»Π΅Π΅ ΡΡΠΆΠ΅Π»ΡΠΌ ΡΠ΅ΡΠ΅Π½ΠΈΠ΅ΠΌCOVID-19. ΠΠΎΠΊΠ°Π·Π°Π½ΠΎ Π½Π°Π»ΠΈΡΠΈΠ΅ ΡΠ΅Π»Π΅Π²ΡΡ
ΠΊΠΎΠ½ΡΠΈΠ½Π³Π΅Π½ΡΠΎΠ² ΡΡΠ΅Π΄ΠΈ ΡΠΎΡΠΈΠ°Π»ΡΠ½ΡΡ
ΠΈΠΏΡΠΎΡΠ΅ΡΡΠΈΠΎΠ½Π°Π»ΡΠ½ΡΡ
Π³ΡΡΠΏΠΏ Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡ,ΠΊΡΠΈΡΠ»Ρ ΠΊΠΎΡΠΎΡΡΡ
ΡΠ»Π΅Π΄ΡΠ΅Ρ ΠΎΡΠ½Π΅ΡΡΠΈ ΠΌΠ΅Π΄ΠΈΡΠΈΠ½ΡΠΊΠΈΡ
ΡΠ°Π±ΠΎΡΠ½ΠΈΠΊΠΎΠ², ΠΏΠ΅Π½ΡΠΈΠΎΠ½Π΅ΡΠΎΠ², ΡΠ°Π±ΠΎΡΠ½ΠΈΠΊΠΎΠ² ΠΎΠ±ΡΠ°Π·ΠΎΠ²Π°ΡΠ΅Π»ΡΠ½ΡΡ
ΡΡΡΠ΅ΠΆΠ΄Π΅Π½ΠΈΠΉ, ΠΏΡΠ°Π²ΠΎΠΎΡ
ΡΠ°Π½ΠΈΡΠ΅Π»ΡΠ½ΡΡ
ΠΎΡΠ³Π°Π½ΠΎΠ², ΡΡΠ°Π½ΡΠΏΠΎΡΡΠ°, ΠΊΠΎΡΠΎΡΡΠ΅ ΡΡΠ΅Π±ΡΡΡ ΠΎΡΠΎΠ±ΠΎΠ³ΠΎ Π²Π½ΠΈΠΌΠ°Π½ΠΈΡΠΈΠΌΠ΅Π΄ΠΈΠΊΠΎ-ΡΠΎΡΠΈΠ°Π»ΡΠ½ΠΎΠΉ ΠΏΠΎΠ΄Π΄Π΅ΡΠΆΠΊΠΈ.
ΠΠ°ΠΊΠ»ΡΡΠ΅Π½ΠΈΠ΅.ΠΡΠΎΠ²Π΅Π΄Π΅Π½Π½ΡΠΉ Π°Π½Π°Π»ΠΈΠ· ΠΏΠΎΠΊΠ°Π·Π°Π»,ΡΡΠΎΠΌΠ°ΡΡΡΠ°Π±Π½ΠΎΠ΅ ΡΠ°ΡΠΏΡΠΎΡΡΡΠ°Π½Π΅Π½ΠΈΠ΅ COVID-19 ΡΡΠ΅Π±ΡΠ΅Ρ ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½ΠΈΡ ΡΠ³Π»ΡΠ±Π»Π΅Π½Π½ΡΡ
ΡΠΏΠΈΠ΄Π΅ΠΌΠΈΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΉΠΈΡΠ°Π·ΡΠ°Π±ΠΎΡΠΊΠΈ Π΄ΠΎΠΏΠΎΠ»Π½ΠΈΡΠ΅Π»ΡΠ½ΡΡ
ΠΏΡΠΎΡΠΈΠ²ΠΎΡΠΏΠΈΠ΄Π΅ΠΌΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΌΠ΅ΡΠΎΠΏΡΠΈΡΡΠΈΠΉΡΡΡΠ΅ΡΠΎΠΌ Π΄ΠΈΠ½Π°ΠΌΠΈΠΊΠΈ Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π΅ΠΌΠΎΡΡΠΈ ΡΡΠΎΠΉ ΡΠΎΡΠΈΠ°Π»ΡΠ½ΠΎ Π·Π½Π°ΡΠΈΠΌΠΎΠΉ ΠΈΠ½ΡΠ΅ΠΊΡΠΈΠ΅ΠΉ