Sleep Difficulties in Infants at Risk for Developmental Delays: A Longitudinal Study
Bibliographic record
Abstract
OBJECTIVES: We compared the sleep of infants at risk for neuromotor delays to that of infants without such risks, and examined the predictive validity of risk indicators to the development of sleep problems. METHODS: Conveniently recruited infants (n = 142) were assessed for neuromotor achievements and sleep behaviors at 4-6 months and 10-12 months of age. Assessment tools were the Harris Infant Neuromotor Test and Morrell's Infant Sleep Questionnaire. Based on a cumulative risk index, three groups were defined: higher risk (n = 28), lower risk (n = 42), and no risk (n = 72). RESULTS: At both ages, the sleep scores were similar among the groups. In the no risk and lower risk group, sleep difficulties decreased with age, while for infants in the higher risk group, more difficulties were reported over time. Overall, the neuromotor attainments were not related to sleep fragmentation or settling difficulties. CONCLUSIONS: In a diverse sample of infants, with and without risks for developmental delays, overall, sleep patterns were similar. It appears that the neuromotor achievements are not associated with sleep-wake regulation, as measured by caregivers' report.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".