Bibliographic record
Abstract
Purpose: The purpose of the study was to compare the cognitive flexibility, resilience and life expectancy of parents with autistic children and the parents of healthy children.Methodology: The method was descriptive with causal-comparative design.The population was all parents of children with autism admitted to the treatment and rehabilitation centers for pervasive developmental disorders (PDD) patients in Tehran in 2017, who were 200 people.Non-probability convenient sampling method was used and 50 mothers with autistic children who had at least high school diploma, willingness, and informed consent to participate in the study were selected as the sample.For the normal-group sample, a sample of 50 people was selected in proportion to the demographic characteristics of the population with disorder.The data were collected using the standard questionnaires of Cognitive Flexibility Inventory (CFI) of Dennis and Vander Wal (2010), Conner-Davidson Resilience scale (CD-RISC) (2003), and Miller Hope Scale (MHS) (1988).Descriptive statistics such as mean and variance and inferential statistics such as multivariate analysis of variance were used for data analysis.Results: The results showed that cognitive flexibility, resilience and life expectancy of autistic children's parents differed from the parents of healthy children and their status in these variables is lower than that of the normal children's parents.Conclusion: According to the results, one can conclude that children's suffering from autism can have negative effects on their parents' psychological status, especially in terms of cognitive flexibility, resilience and life expectancy.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.943 | 0.928 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".