Development and Initial Feasibility Testing of Brief Cognitive-Behavioral Therapy for Insomnia in Adolescents With Comorbid Conditions
Bibliographic record
Abstract
Insomnia is highly prevalent in the adolescent population and frequently occurs in the context of other medical or mental health concerns. Efficacy of cognitive–behavioral therapy for insomnia (CBT-I) has been determined in adults with comorbid conditions. However, there are limited data applying CBT-I to adolescents with comorbid conditions. Therefore, the purpose of this study was to (a) develop and refine a 4-session CBT-I intervention for adolescents with co-occurring medical and mental health conditions, and (b) evaluate feasibility and acceptability of applying the intervention to adolescents and their parents. Forty participants (ages 11 to 18 years) were recruited from 2 pediatric specialty clinics representing a range of physical and psychiatric comorbidities (e.g., depression, chronic pain, anxiety). Adolescents and parents attended 4 treatment sessions of CBT-I delivered individually or conjointly to adolescent and parent. Daily sleep diaries were completed during the treatment period. Preliminary findings demonstrated a high level of feasibility and acceptability of treatment. Compliance with treatment visits was high, with 34 of the 40 families (85%) completing all 4 sessions. Youth and parents were highly engaged in therapy sessions as rated by treating therapists. On the Treatment Evaluation Inventory, parents’ and teens’ mean scores indicated high treatment acceptability ( M = 38.8, SD = 5.2; M = 36.8, SD = 4.6, respectively). The preliminary data suggest that CBT-I is feasible to implement to treat insomnia in adolescents with co-occurring health and mental health conditions. Future studies are needed to evaluate intervention efficacy on sleep and functional outcomes in youth.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".