The Impact of Parental Psychiatric Symptoms and Parent-Child Relationships on Behavioural and Emotional Problems in Newly-Diagnosed Toddlers and Preschool Children with Autism Spectrum Disorders
Bibliographic record
Abstract
Background: Emotional and behavioural problems occur at a high rate in children with autism spectrum disorders (ASD). These problems are associated with a broad range of risk factors such as parental psychopathology and family environment in school-age children and adolescents. However, limited information is available about these phenomena in toddlers and preschool children. This cross-sectional study examined the association of maternal and paternal psychiatric symptoms and mother-child relationships with emotional and behavioural problems and socioemotional competence of newly-diagnosed young children with ASD. Method: Autistic symptoms, developmental level, and mother-child relationship of children were evaluated. Parents completed a checklist on child behavioural and emotional problems, and individual questionnaires on their own mental health. Results: Participants were 35 children with ASD aged 18 – 53 months, referred to an infant mental health clinic. Maternal hostility and poor mother-child relationships have been found to be independently associated with emotional and behaviour problems in these children. Conclusions: This study suggests that maternal hostility and mother-child relationship problems may play a role for the development of emotional and behaviour problems in toddlers and preschool children with ASD.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".