A Practice Pathway for the Identification, Evaluation, and Management of Insomnia in Children and Adolescents With Autism Spectrum Disorders
Bibliographic record
Abstract
OBJECTIVE: This report describes the development of a practice pathway for the identification, evaluation, and management of insomnia in children and adolescents who have autism spectrum disorders (ASDs). METHODS: The Sleep Committee of the Autism Treatment Network (ATN) developed a practice pathway, based on expert consensus, to capture best practices for an overarching approach to insomnia by a general pediatrician, primary care provider, or autism medical specialist, including identification, evaluation, and management. A field test at 4 ATN sites was used to evaluate the pathway. In addition, a systematic literature review and grading of evidence provided data regarding treatments of insomnia in children who have neurodevelopmental disabilities. RESULTS: The literature review revealed that current treatments for insomnia in children who have ASD show promise for behavioral/educational interventions and melatonin trials. However, there is a paucity of evidence, supporting the need for additional research. Consensus among the ATN sleep medicine committee experts included: (1) all children who have ASD should be screened for insomnia; (2) screening should be done for potential contributing factors, including other medical problems; (3) the need for therapeutic intervention should be determined; (4) therapeutic interventions should begin with parent education in the use of behavioral approaches as a first-line approach; (5) pharmacologic therapy may be indicated in certain situations; and (6) there should be follow-up after any intervention to evaluate effectiveness and tolerance of the therapy. Field testing of the practice pathway by autism medical specialists allowed for refinement of the practice pathway. CONCLUSIONS: The insomnia practice pathway may help health care providers to identify and manage insomnia symptoms in children and adolescents who have ASD. It may also provide a framework to evaluate the impact of contributing factors on insomnia and to test the effectiveness of nonpharmacologic and pharmacologic treatment strategies for the nighttime symptoms and daytime functioning and quality of life in ASD.
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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 | 0.033 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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".