Practice guideline: Treatment for insomnia and disrupted sleep behavior in children and adolescents with autism spectrum disorder
Bibliographic record
Abstract
OBJECTIVE: To review pharmacologic and nonpharmacologic strategies for treating sleep disturbances in children and adolescents with autism spectrum disorder (ASD) and to develop recommendations for addressing sleep disturbance in this population. METHODS: The guideline panel followed the American Academy of Neurology 2011 guideline development process, as amended. The systematic review included studies through December 2017. Recommendations were based on evidence, related evidence, principles of care, and inferences. MAJOR RECOMMENDATIONS LEVEL B: For children and adolescents with ASD and sleep disturbance, clinicians should assess for medications and coexisting conditions that could contribute to the sleep disturbance and should address identified issues. Clinicians should counsel parents regarding strategies for improved sleep habits with behavioral strategies as a first-line treatment approach for sleep disturbance either alone or in combination with pharmacologic or nutraceutical approaches. Clinicians should offer melatonin if behavioral strategies have not been helpful and contributing coexisting conditions and use of concomitant medications have been addressed, starting with a low dose. Clinicians should recommend using pharmaceutical-grade melatonin if available. Clinicians should counsel children, adolescents, and parents regarding potential adverse effects of melatonin use and the lack of long-term safety data. Clinicians should counsel that there is currently no evidence to support the routine use of weighted blankets or specialized mattress technology for improving disrupted sleep. If asked about weighted blankets, clinicians should counsel that the trial reported no serious adverse events with blanket use and that blankets could be a reasonable nonpharmacologic approach for some individuals.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".