Early adversity and family resilience factors in children with autism spectrum disorder: A narrative review
Bibliographic record
Abstract
Global estimates indicate that autism is a neurodevelopmental condition that is currently diagnosed in 1 in 100 people across the world. Autistic children can experience deficits in social communication, often linked to difficulties with joint attention and facial emotion recognition. Restrictive repetitive behaviors and interests (RRBIs) are also part of the diagnostic criteria of autism and are associated with lower adaptive skills. Due to social challenges and RRBIs exhibited by autistic children, they may be at higher risk for experiencing social and familial stressors. In non-autistic children, early adversity is predictive of deficits in executive functioning, neurological changes, and poor adult health. However, resilience factors have been identified, which can offset the negative impacts of adversity. In autistic children, these protective factors may have differential downstream influences on children's outcomes due to cognitive and social difficulties. In this narrative review, we report that autistic children are more likely to experience familial and environmental stressors compared to non-autistic children. Resilience factors such as positive parenting, sleep, social relationships, and executive functioning skills were identified as key areas for future research. Lay summary Children with autism are statistically more likely than their peers to be exposed to adverse childhood events including bullying, parental divorce, and poverty. The more severely affected a child is by autism the greater the likelihood they will be exposed to early life stress. This indicates that the most vulnerable children with autism who have limited adaptive skills to promote resilience to stress may have the highest exposure to stressful events during their childhood. In turn, a better understanding of how early adversity impacts children with autism is needed as well to characterize resilience factors that promote optimal outcomes. In this review of the literature, it was found that children with autism may experience more stress from their family and surroundings compared to children without autism. Factors that can help these children cope better were identified, including supportive parenting, getting enough sleep, having friends, and having good problem-solving skills. This research could help parents and teachers better understand how to support children with autism who are experiencing early adversity.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".