Longitudinal study of childhood sleep trajectories and adolescent mental health problems
Bibliographic record
Abstract
Abstract Study Objective To investigate whether childhood sleep trajectories are associated with mental health symptoms such as social phobia, generalized anxiety, depression, attention deficit hyperactivity disorder (ADHD), conduct problems, and opposition at age 15. Methods A total of 2120 children took part in the Quebec Longitudinal Study of Child Development. Childhood sleep trajectories were computed from maternal reports at 2.5, 3.5, 4, 6, 8, 10, and/or 12 years. At age 15, 1446 adolescents filled out mental health and sleep questions. A path analysis model was assessed in the full sample. Results Four childhood nocturnal sleep duration trajectories were identified: (1) a short pattern (7.5%), (2) a short-increasing pattern (5.8%), (3) a 10 hours pattern (50.7%), and (4) an 11 hours pattern (36.0%). Three childhood sleep latency trajectories were found: (1) a short pattern (31.7%), (2) an intermediate pattern (59.9%), and (3) a long pattern (8.4%). Finally, two childhood wakefulness after sleep-onset trajectories were found: (1) a normative pattern (73.0%) and (2) a long pattern (27.0%). The path analysis model indicated that children following a long childhood sleep latency trajectory were more likely to experience symptoms of depression (β = 0.06, 95% CI: 0.01 to 0.12), ADHD (β = 0.07, 95% CI: 0.02 to 0.13), conduct problems (β = 0.05, 95% CI: 0.00 to 0.10) and opposition (β = 0.08, 95% CI: 0.02 to 0.13) at age 15. Conclusions This longitudinal study revealed that children presenting a long sleep latency throughout childhood are at greater risk of symptoms of depression, ADHD, conduct problems, and opposition in adolescence.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".