Child and adolescent sleep disturbances and psychopathology in a mental health clinic sample
Bibliographic record
Abstract
Introduction Children and adolescents treated in specialty mental health services are more likely to have sleep disturbances than those without mental health problems. Few studies have investigated the relationship between sleep and psychopathology in broad clinical samples of children. We examined the relationship between sleep disturbance and age on internalizing and externalizing psychopathology in a sample who sought treatment at children's mental health centers. Methods Secondary data analyses were completed on a sample of children (N = 13,472; aged 4 to 18; 55% male) from 39 children's mental health agencies in Ontario, Canada, who completed a semi-structured assessment, the interRAI Children and Youth Mental Health (ChYMH). A split-half sample approach was utilized (S1 n = 6,773, S2 n = 6,699). Hierarchical regressions examined the effects of sleep disturbances (i.e., difficulty falling asleep, staying asleep, night waking, bedtime resistance, falling asleep during the day) on internalizing and externalizing symptoms, above and beyond established child- (i.e., age, sex, sensory sensitivity, pain) and family-level variables (family functioning, caregiver distress, parenting strengths). Age was tested as a moderator for sleep disturbances on both outcome variables. Results Overall, 6.7% of children had clinically significant sleep disturbance scores (≥10 out of 16) on the interRAI ChYMH. In both samples, sleep disturbances predicted internalizing (S1 ΔR2 = 10%, S2 ΔR2 = 10%) and externalizing symptoms (S1 ΔR2 = 2%, S2 ΔR2 = 1%), above and beyond child and family variables. Age moderated the relationship between sleep disturbances and internalizing symptoms (S1 ß = 0.07; S2 ß = 0.07; ΔR2 = 0.004 in both samples), but not externalizing symptoms; sleep disturbance was more strongly related to internalizing symptoms amongst adolescents (ß = 0.98) than children (ß = 0.62). Discussion The relationship between sleep and internalizing symptoms appears to change as children move through development. Further, sleep was a stronger predictor of internalizing problems in adolescents than children, suggesting an additional focus of clinician efforts in this age group. These findings strengthen the importance of routine assessment of sleep, as is done with the interRAI ChYMH.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.002 | 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".