0930 A SYSTEMATIC REVIEW OF SLEEP QUANTITY, SLEEP QUALITY, SLEEPINESS, AND FATIGUE OUTCOMES FOR PARENTS OF CHILDREN WITH NEURODEVELOPMENTAL DISABILITIES
Bibliographic record
Abstract
Sleep problems are common in children with Neurodevelopmental Disabilities (NDDs), with estimates ranging from 25% to 86% (Wiggs, 2001). Short sleep duration, frequent nighttime wakes, and bedtime resistance interfere with parental sleep and aspects of daytime functioning. No previous comprehensive systematic reviews examining sleep outcomes in caregivers of children with NDDs have been published. A systematic search of five databases (Cochrane Library, Medline, EBSCOhost CINAHL, PsychINFO, EMBASE) was conducted between June and July 2016. Eligibility criteria included: English, peer-reviewed, full-text journal reports; any study design, except case reports; sample including parent caregivers of a child with a NDD; sleep quantity, sleep quality, sleepiness, and/or fatigue outcomes reported. Studies were appraised using the NHLBI Quality Assessment tools. Of 7534 citations retrieved, 7444 were removed after screening titles and abstracts for duplicates and exclusion criteria. Screening the 90 remaining full texts left 33 meeting eligibility criteria. Most (n=27) were cross-sectional, included a range of NDDs and were of “poor” (n=14) or “fair” (n=17) quality. One of two “good” quality studies found parents of children with NDDs slept significantly fewer minutes at night than parents with typically developing children (TD). Parents of children with NDDs consistently reported (n=10 studies) significantly poorer subjective sleep quality using the Pittsburgh Sleep Quality Index. No studies compared sleepiness across samples, and fatigue was not measured consistently across studies. Although maternal (n=16) and “parental/caregiver” (n=17) sleep were frequently examined, no studies exclusively reported on paternal sleep. Parents of children with NDDs report significantly poorer sleep quality compared to parents of TD children. There is a paucity of good quality comparative studies, using well-validated measures, that examine sleep duration, daytime sleepiness, and/or fatigue. Future research should aim to fill this gap, providing greater insight to parents’ experiences and identifying targets for intervention design and evaluation. N/A
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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 | 0.007 | 0.035 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.010 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".