Trajectories of reported sleep duration associate with early childhood cognitive development
Bibliographic record
Abstract
STUDY OBJECTIVES: Examine how different trajectories of reported sleep duration associate with early childhood cognition. METHODS: Caregiver-reported sleep duration data (n = 330) were collected using the Brief Infant Sleep Questionnaire at 3, 6, 9, 12, 18, and 24 months and Children's Sleep Habits Questionnaire at 54 months. Multiple group-based day-, night-, and/or total sleep trajectories were derived-each differing in duration and variability. Bayley Scales of Infant and Toddler Development-III (Bayley-III) and the Kaufman Brief Intelligence Test- 2 (KBIT-2) were used to assess cognition at 24 and 54 months, respectively. RESULTS: Compared to short variable night sleep trajectory, long consistent night sleep trajectory was associated with higher scores on Bayley-III (cognition and language), while moderate/long consistent night sleep trajectories were associated with higher KBIT-2 (verbal and composite) scores. Children with a long consistent total sleep trajectory had higher Bayley-III (cognition and expressive language) and KBIT-2 (verbal and composite) scores compared to children with a short variable total sleep trajectory. Moderate consistent total sleep trajectory was associated with higher Bayley-III language and KBIT-2 verbal scores relative to the short variable total trajectory. Children with a long variable day sleep had lower Bayley-III (cognition and fine motor) and KBIT-2 (verbal and composite) scores compared to children with a short consistent day sleep trajectory. CONCLUSIONS: Longer and more consistent night- and total sleep trajectories, and a short day sleep trajectory in early childhood were associated with better cognition at 2 and 4.5 years.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".