Bibliographic record
Abstract
AIM: To investigate prevalence of mental health difficulties and mental disorders among children with cerebral palsy (CP) in Ireland, and identify associated risk factors. METHODS: A cross-sectional survey was conducted with participants aged 6-17 years with CP. Data were collected via a survey that included demographics, CP characteristics, psychopathology (Strengths and Difficulties Questionnaire (SDQ)), mental disorders, physical well-being, and social factors. Linear and logistic regression were used to explore associations between risk factors and mental health outcomes. RESULTS: 330 participants completed the survey. The mean (SD) SDQ total difficulties score was 13.4 (6.6), with 29% of participants being at risk for emotional and behavioural problems and 21% diagnosed with at least one mental disorder, of which anxiety was the most prevalent (14%). Higher SDQ total difficulties scores were associated with intellectual disability, poor sleep, challenges in forming friendships, bullying, and family dysfunction (p < 0.05). Female participants and those with low physical activity participation were more likely to experience mental disorders (p < 0.05). INTERPRETATION: These findings highlight the multiple health and social factors associated with mental health difficulties emphasising the urgent need for targeted mental health interventions for young people with CP in Ireland to enhance overall mental well-being. CLINICAL TRIAL NUMBER: Not applicable.
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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 | 0.003 | 0.009 |
| 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 | 0.000 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.581 | 0.396 |
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".