A Person-Based Web-Based Sleep Intervention Aimed at Adolescents (SleepWise): Randomized Controlled Feasibility Study
Bibliographic record
Abstract
BACKGROUND: Adolescents are advised to sleep 8-10 hours per night; however, most do not sleep for this recommended amount. Poor adolescent sleep is associated with detrimental health outcomes, including reduced physical activity, risk-taking behaviors, and increased depression and anxiety levels, making this an important public health concern. Existing interventions targeting adolescent sleep are often unsuccessful or their effectiveness unclear, as they are frequently noninteractive, time-consuming, and lack a strong theoretical foundation; highlighting an urgent need for innovative interventions deemed acceptable by adolescents. OBJECTIVE: The main objective of this study was to determine the acceptability, feasibility, and preliminary impact of a web-based person-based sleep intervention (SleepWise) on adolescent sleep quality. Participant incentivization was also explored to understand its impact on engagement, acceptability, and sleep quality. METHODS: A feasibility trial was conducted to test the feasibility, acceptability, and preliminary impact of SleepWise on adolescent sleep quality, developed based on the person-based approach to intervention development. In total, 90 participants (aged 13-17 years) from further education institutions and secondary schools were recruited for two 2-arm randomized controlled trials. One trial (trial 1) was incentivized to understand the impact of incentivization. Acceptability and sleep quality were assessed via questionnaires, and a mixed methods process evaluation was undertaken to assess participant engagement and experience with SleepWise. Engagement was automatically tracked by SleepWise, which collected data on the date and time, pages viewed, and the number of goals and sleep logs completed per participant. Semistructured interviews were carried out to gain participant feedback. RESULTS: Participants in both trials reported high levels of acceptability (trial 1: mean 21.00, SD 2.74; trial 2: mean 20.82, SD 2.48) and demonstrated similar levels of engagement with SleepWise. Participants in trial 1 viewed slightly more pages of the intervention, and those in trial 2 achieved their set goals more frequently. Improvements in sleep quality were found in both trials 1 and 2, with medium (trial 1) and large (trial 2) effect sizes. A larger effect size for improvement in sleep quality was found in the nonincentivized trial (d=0.87), suggesting that incentivization may not impact engagement or sleep quality. Both trials achieved acceptable recruitment (trial 1, N=48; trial 2, N=42), and retention at 5 weeks (trial 1: N=30; trial 2: N=30). Qualitative findings showed that adolescents lead busy lifestyles, which may hinder engagement; however, participants deemed SleepWise acceptable in length and content, and made attempts at behavior change. CONCLUSIONS: SleepWise is an acceptable and potentially efficacious web-based sleep intervention aimed at adolescents. Findings from this study showed that incentivization did not greatly impact engagement, acceptability, or sleep quality. Subject to a full trial, SleepWise has the potential to address the urgent need for innovative, personalized, and acceptable sleep interventions for adolescents. TRIAL REGISTRATION: OSF Registries osf.io/yanb2; https://osf.io/yanb2.
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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 | 0.012 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".