Sleep and Sensory Characteristics in Young Children With Fetal Alcohol Spectrum Disorder
Bibliographic record
Abstract
BACKGROUND: : Fetal alcohol spectrum disorder (FASD) is a syndrome that results from prenatal alcohol exposure and is defined by significant neurobehavioral impairments. Sleep disruption has been recognized as a clinically important symptom of FASD that has multiple negative effects on the child's health, ability to function adaptively, as well as on family and caregivers. However, few studies have addressed and characterized the sleep problems in this population. OBJECTIVE: : The objective of this study was to characterize sleep in FASD and describe the impact of sensory processing difficulties on sleep patterns in children with FASD. METHODS: : Children with FASD were compared with age-matched typically developing children between 3 and 6 years of age. Sleep was assessed using actigraphy, a sleep log, and the Children's Sleep Habits Questionnaire. The Sensory Profile™, completed by caregivers, was used to evaluate the child's sensory processing abilities. Overall differences in sensory processing were correlated with actigraphic parameters measured in alcohol exposed and control groups. RESULTS: : Data show that children with FASD have significantly more sleep disturbances than typically developing children, including increased bedtime resistance, shortened sleep duration, increased sleep anxiety, and increased night awakenings and parasomnias. Actigraphy reveals a significant difference between groups for sleep onset latency. CONCLUSIONS: : This study demonstrates that sensory processing deficits are widespread in children with FASD and that these deficits are associated with multiple sleep problems. Children with FASD should be screened for sleep-related disorders and would benefit from occupational therapy for sensory-based treatment aimed at sleep regulation and consolidation.
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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 | 0.001 |
| 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 | 0.000 | 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".