Relation between quality of life and physical literacy of young adolescents with Autism Spectrum Disorder
Bibliographic record
Abstract
This study aims to obtain knowledge of how ASD individuals differ from their normally developed equals in terms of physical literacy and quality of life on a stage of early adolescents. Data have been collected from two samples: 18 males with autism spectrum disorders (ASD) aged 11–13 years (main group) and 30 males aged 11–12 years without ASD diagnosis (control group, CG). Canadian Assessment of Physical Literacy – second edition (CAPL-2) has been applied for assessing the level of physical literacy. Pediatric Quality of Life Inventory (PedsQL™4.0) has been used to assess the quality of life. Children with ASD have the most significant lag in static strength endurance of muscles (84%), coordination, dynamic, and static balance lag behind the standard (by 67% to 45%). The quality of life following the Emotional Functioning scale is relatively low both in children with ASD (58.42 ± 19.51 points) and healthy respondents (69.50 ± 17.04 points). Respondents with ASD indicate that it is hard to establish good relationships with other children (47.37%), had complaints about bullying (21.05%), and maintain the required pace of the game (68.43%). Physical education programs should focus more on coping with disabled children in the integration environment and better preparation of ASD children for physical activity which requires social interaction like playing sports games.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".