Evaluation of a School-Based Intervention for Adolescent Sleep Problems
Bibliographic record
Abstract
STUDY OBJECTIVES: The present study investigated the effectiveness of a school-based intervention in increasing sleep knowledge and improving adolescent sleep problems. DESIGN: A randomized, controlled trial using 2 groups (program class, classes-as-usual: [CAU]) assessed over 3 time points (pre-program, post-program, 6-week follow-up). PARTICIPANTS/SETTING: Eighty-one students (mean age = 15.6 +/- 0.6 y; 33% male) from 2 schools in South Australia. Schools provided one class to participate in the sleep intervention program (N = 41) and a second class to act as a control class (N = 40). INTERVENTION: Four 50-minute classes across a 4-week period. Classes consisted of educating adolescents on promoting and maintaining a healthy lifestyle based on a cognitive-behavior therapy framework. MEASUREMENTS AND RESULTS: Data were collected pre-program, post-program, and at 6-week follow-up using an online questionnaire. Qualitative student and teacher data were collected at post-program. Baseline data indicated sleep problems were prevalent (53.1% insufficient sleep on school nights [< 8 h] and 77.8% discrepant school/weekend rise times [> 2 h]). These 2 criteria identified 36 adolescents with a delayed sleep timing (DST; Program, N = 21; CAU, N = 15). The program increased sleep knowledge (P = 0.001); however, analyses revealed no significant effects on target sleep variables as compared with the CAU class for the entire group (all P > 0.05). For DST adolescents, there was a significant interaction for reducing the discrepancy between school and weekend out of bed times (P = 0.002). There was no impact on other sleep parameters or depressed mood. CONCLUSIONS: School-based sleep interventions for adolescents are a novel method for addressing a prevalent problem. Future programs should develop ways to motivate adolescents to change sleep practices.
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 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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".