Medications for sleep disturbance in children and adolescents with depression: a survey of Canadian child and adolescent psychiatrists
Bibliographic record
Abstract
BACKGROUND: Primary care physicians and child and adolescent psychiatrists often treat sleep disturbances in children and adolescents with mood disorders using medications off-label, in the absence of clear evidence for efficacy, tolerability and short or long-term safety. This study is the first to report Canadian data about prescribing preferences and perceived effectiveness reported by child and adolescent psychiatrists regarding medications used to manage sleep disturbances in children and adolescents with depression. METHODS: Canadian child and adolescent psychiatrists were surveyed on their perception of effectiveness of a range of medications commonly prescribed for sleep disturbances, their ranked preferences for these medications, reasons for avoiding certain medications, and perceived side effects. RESULTS: Sixty-seven active child and adolescent psychiatrists completed the survey. Respondents reported noting significant sleep issues in 40% of all their patients. Melatonin and trazodone were identified as the first treatment of choice by 83% and 10% of respondents respectively, and trazodone was identified as the second treatment of choice by 56% of respondents for treating sleep disturbances in children and adolescents with depression. Melatonin (97%), trazodone (81%), and quetiapine (73%) were rated by a majority of respondents as effective. Doxepin, zaleplon, tricyclic antidepressants, zolpidem, or lorazepam were rarely prescribed due to lack of evidence and/or concerns about adverse effects, long-term safety, suitability for youth, suicidality, and dependence/tolerance. CONCLUSIONS: Melatonin and certain off-label psychotropic drugs are perceived as being more effective and appropriate to address sleep disturbances in children and adolescents with depression. More empirical evidence on the efficacy, tolerability and indications for using these medications and newer group of sleep medications in this population is needed.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".