Sleep in youth with autism spectrum disorders: systematic review and meta-analysis of subjective and objective studies
Bibliographic record
Abstract
Background Sleep problems are common and impairing in individuals with autism spectrum disorders (ASD). Evidence synthesis including both subjective (ie, measured with questionnaires) and objective (ie, quantified with neurophysiological tools) sleep alterations in youth with ASD is currently lacking. Objective We conducted a systematic review and meta-analysis of subjective and objective studies sleep studies in youth with ASD. Methods We searched the following electronic databases with no language, date or type of document restriction up to 23 May 2018: PubMed, PsycInfo, Embase+Embase Classic, Ovid Medline and Web of Knowledge. Random-effects models were used. Heterogeneity was assessed with Cochran’s Q and I2 statistics. Publication (small studies) bias was assessed with final plots and the Egger’s test. Study quality was evaluated with the Newcastle Ottawa Scale. Analyses were conducted using Review Manager and Comprehensive Meta-Analysis. Findings From a pool of 3359 non-duplicate potentially relevant references, 47 datasets were included in the meta-analyses. Subjective and objective sleep outcome measures were extracted from 37 and 15 studies, respectively. Only five studies were based on comorbidity free, medication-naïve participants. Compared with typically developing controls, youth with ASD significantly differed in 10/14 subjective parameters and in 7/14 objective sleep parameters. The average quality score in the Newcastle-Ottawa Scale was 5.9/9. Discussion and clinical implications A number of subjective and, to a less extent, objective sleep alterations might characterise youth with ASD, but future studies should assess the impact of pharmacological treatment and psychiatric comorbidities.
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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 | 0.020 | 0.046 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.039 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".