Quality of Life of Mothers of Children With Autism Spectrum Disorders and Its Relationship With Severity of Disorder and Child’s Occupational Performance
Bibliographic record
Abstract
Introduction: Mothers of children with Autism Spectrum Disorders (ASD) have the lowest grade of quality of life compared with mothers of children with other disorders like mental retardation, learning disorders, or physical impairments. To the best of our knowledge, there is no study on the influence of severity of disorder and occupational performance of autistic child on mother’s quality of life. This study aims to determine the relationship between quality of life of these mothers with severity of disorder and occupational performance in their autistic children. Materials and Methods: The participants included 35 mothers and their children with ASD (aged 3 to 7 years). They were selected by available sampling method from Tehran City, Iran. Severity of disorder and occupational performance were respectively measured by Gilliam Autism Rating Scale 2 and Canadian Occupational Performance Measure. Results: The relationship between mothers’ quality of life and severity of their children’s ASD was significant (except for two components of physical roles [P=0.276] and bodily pains [P=0.174]. Also correlation of mothers’ quality of life and occupational performance was significant (except for four dimensions of physical functioning [P=0.439] , physical roles [P=0.801], bodily pains [P=0.105] and role emotional [P=0.140]). Conclusion: The results show that quality of life of mothers of autistic children is significantly associated with severity of disorder and occupational performance of children, but its relationship with severity of disorder is more pronounced than occupational performance. Therefore, in order to improve mother’s quality of life, the severity of symptoms of ASD should be decreased and child’s occupational performance increased.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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".