Occupational performance of children with autism spectrum disorder and quality of life of their mothers
Bibliographic record
Abstract
OBJECTIVES: Limited studies were found to investigate the occupational performance of autistic children and their parents' quality of life. Therefore, this study aimed to investigate occupational performance of children with Autism Spectrum Disorder (ASD) and QoL of their mothers. RESULTS: In this study, 88 participants were selected from autism centers in Arak, Iran, 2020. The Canadian Occupational Performance Measure (COPM) and the parent version of Quality of Life in Autism Questionnaire (QoLA-P) were used to assess the occupational performance of ASD children and their mothers QoL. QoLA-P consists of parts A which is related to the quality of life and part-B related to the problems that these children have and are related to the parents or their caregivers. Regarding occupational performance, the first priority of mothers is self-care with frequency 64.8%. The finding suggested a significant correlation between total function score of COPM and the score of part-A (r = 0.227, p = 0.033) of QoLA-P. Also, the results revealed a significant correlation between the total satisfaction score of COPM and the score of part-A (r = 0.236, p = 0.026) and part-B of QoLA-P questionnaire (r = 0.231, p = 0.030). The mothers' first priority is self-care and, the total satisfaction and function score of COPM showed a significant correlation with mothers' QoL.
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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 | 0.001 | 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 | 0.000 | 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".