Chronicity of mental comorbidity in children with new‐onset physical illness
Bibliographic record
Abstract
BACKGROUND: Evidence suggests that physical and mental illnesses are strongly correlated in children. This study examined patterns of the chronicity of multimorbidity (co-occurring physical and mental illness); estimated homotypic continuity; and modelled factors associated with chronicity in children newly diagnosed with a chronic physical illness. METHODS: Children aged 6-16 years diagnosed with one of asthma, diabetes, epilepsy, food allergy, or juvenile arthritis were recruited from two children's hospitals and followed for 6 months. Child mental illness was measured using the parent-reported Mini International Neuropsychiatric Interview and Ontario Child Health Study Emotional Behavioural Scales at baseline and 6 months later. Children were stratified into three groups: no multimorbidity, acute (multimorbidity at only one assessment), and persistent (multimorbidity at both assessments). RESULTS: Forty-nine children were available for analysis: no multimorbidity (n = 18), acute (n = 13), and persistent (n = 18). Homotypic continuity was highest for conduct disorder (67.5%) and lowest for major depression (16.7%). Unadjusted analyses showed positive associations between child and parent behavioural symptoms, as well as family functioning with persistent multimorbidity. These associations remained after adjustment, ranging from odds ratio (OR) = 1.29 [1.01, 1.64] for depression to OR = 1.61 [1.11, 2.33] and OR = 1.61 [1.10, 2.35] for attention-deficit hyperactivity and oppositional defiant, respectively, in child models. In parent models, associations remained for parental anxiety (OR = 1.18 [1.04, 1.34]) and stress (OR = 1.15 [1.02, 1.31]). CONCLUSIONS: Multimorbidity is persistent in children newly diagnosed with physical illnesses, regardless of the mental comorbidity experienced. Integrating family-centred mental health services soon after the diagnosis of a physical illness should be prioritized in pediatric settings.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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".