Subtyping at‐risk adolescents for predicting response toward insomnia prevention program
Bibliographic record
Abstract
BACKGROUND: Previous study has shown that a brief cognitive-behavioral prevention insomnia program could reduce 71% risk of developing insomnia among at-risk adolescents. This study aimed to evaluate the differential response to insomnia prevention in subgroups of at-risk adolescents. METHODS: Adolescents with a family history of insomnia and subthreshold insomnia symptoms were randomly assigned to a 4-week insomnia prevention program or nonactive control group. Assessments were conducted at baseline, 1 week, and 6- and 12-month after the intervention. Baseline sleep, daytime, and mood profiles were used to determine different subgroups by using latent class analysis (LCA). Analyses were conducted based on the intention-to-treat approach. RESULTS: LCA identified three subgroups: (a) insomnia symptoms only, (b) insomnia symptoms with daytime sleepiness and mild anxiety, and (c) insomnia symptoms with daytime sleepiness, mild anxiety, and depression. The incidence rate of insomnia disorder over the 12-month follow-up was significantly reduced for adolescents receiving intervention in subgroup 3 compared with the controls (hazard ratio [HR] = 0.37; 95% confidence interval [CI]: 0.13-0.99; p = .049) and marginally for subgroup 2 (HR = 0.14; 95% CI: 0.02-1.08; p = .059). In addition, adolescents who received intervention in subgroups 2 and 3 had a reduced risk of excessive daytime sleepiness (subgroup 2: adjusted OR [AdjOR] = 0.45, 95% CI: 0.23-0.87; subgroup 3: AdjOR = 0.32, 95% CI: 0.13-0.76) and possible anxiety (subgroup 2: AdjOR = 0.47, 95% CI: 0.27-0.82; subgroup 3: AdjOR = 0.33, 95% CI: 0.14-0.78) compared with the controls over the 12-month follow-up. CONCLUSIONS: Adolescents at risk for insomnia can be classified into different subgroups according to their psychological profiles, which were associated with differential responses to the insomnia prevention program. These findings indicate the need for further phenotyping and subgrouping at-risk adolescents to develop personalized insomnia prevention.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".