119: Sleep Disorders Associated with Attention Problems in Adopted Children
Bibliographic record
Abstract
Sleep problems occur in up to 25% of children and are more prevalent in children who have symptoms of inattention/hyperactivity as well as those who are insecurely attached to their caregivers. Studies show that foster children display sleep problems, but limited research exists on the prevalence and etiology of specific sleep disorders in adopted children. To investigate the relationships between psychosocial factors and the incidence of sleep disorders in adopted children. Participants were recruited through a notice sent to parents on an adoption council listserv and through discussion with families attending a social service meeting. Families were eligible to participate if their child was between two and seven years of age. Thirty parent questionnaires, measuring demographics, behavior, parent/child relationships, and sleep problems, were sent to families. Responses were analyzed using descriptive statistics and correlations. T-tests were used comparing children reported to be good vs. poor-sleepers. A total of 67% responded (n=20). Twelve children (60%) had sleep problems based on the Children's Sleep Habits Questionnaire. As compared to good-sleepers, those reporting sleep problems experienced more parasomnias (P<0.002) and trends to issues with sleep onset delay and sleep duration. Children with sleep disorders also had more attention problems (P<0.025), which correlated significantly with parental attachment scores (r=−0.69, P=0.01). Sleep disorders (especially parasomnias) were frequently reported in adopted children. Those reporting sleep disorders showed more attention problems, which were associated with lower levels of parental attachment. Further research in this area will help to develop targeted interventions to prevent sleep disorders in adopted children.
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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 | 0.002 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".