“Box Box on the Shelve! Tell Me!”: The Effects of Adapted Plays on Physical Fitness in Autism Spectrum Disorder
Bibliographic record
Abstract
The purpose of this study is to examine the effects of adapted play activities on physical fitness in individuals with autism spectrum disorder (ASD). In this study, the pretest-posttest design with a single experimental group was used. The sample of the study is comprised of 7 students with 7–13 years of age. In the measurement of physical fitness parameters of children with ASD, height, body weight, flexibility, vertical jump, and right/left hand grasping power tests were performed. SPSS 23.0 program was used. In addition to descriptive statistics, Wilcoxon signed rank test was used in the comparisons of pretest-posttest measurements. According to the findings of the research, among the physical fitness parameters, it was determined that there were statistically significant differences in the flexibility, vertical jumping, right and left-hand grasping power values, while there was statistically no significant difference concerning the body mass index values. We can mention that the obtained findings demonstrate that play activities lesson program has positive impacts on the physical fitness parameters of children with ASD, and it contributes to their motor developments. Additionally, this research study is considered significant since it leads the way for researchers and teachers of this field and it provides an insight for further studies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".