A Study of the Wellbeing of Siblings of Children with Autism Spectrum Disorders: Sibling Efficacy, Positive and Negative Affect, and Coping Strategies
Bibliographic record
Abstract
Autism spectrum disorders (ASD) include pervasive developmental disorders characterised by communication deficits, difficulty with social understanding, and repetitive behaviors. Few studies have compared the efficacy, affect, and coping strategies of siblings of typically developing children with siblings of children with ASD. Typically developing siblings are understood to be at an increased risk of externalising and internalising problems. The current study examined whether siblings of children with ASD differed in levels of efficacy, affect, and coping from siblings of typically developing children. Participants (156) included an Australia-wide sample involving 82 siblings of children with ASD, and 74 siblings of typically developing individuals. Participants completed The Self-Efficacy Scale for Children (assessing social, emotional, and academic efficacy), the Positive and Negative Affect Scales, the Brief COPE Scale, and other scales as part of the larger study. Results showed that ASD siblings reported lower scores on emotional efficacy, social efficacy, and positive affect, and higher negative affect, than did the comparison group siblings. However, no significant differences were found in coping strategies or academic efficacy between the ASD siblings and the typically developing siblings. Consistent with earlier research findings, there are perceived negative effects or risks from being a sibling of an individual with ASD, suggesting support interventions may assist the development of emotional and social efficacy and increased positive affect for these individuals.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".