Restoring effective sleep tranquility (REST): A feasibility and pilot study
Bibliographic record
Abstract
Introduction The purpose of this pilot study was to establish the feasibility of completing a future controlled trial of a multi-component cognitive behavioral therapy for insomnia program for military veterans with sleep disturbance. Method This was a single-arm feasibility and pilot study. Participants were United States post-9/11 veterans with service-connected injuries, university students, and had self-reported sleep disturbances. Restoring Effective Sleep Tranquility was a multi-component cognitive behavioral therapy for insomnia intervention consisting of seven sessions of group therapy and eight 1:1 sessions delivered by occupational therapists. Feasibility and pilot indicators were process, resources, management, and scientific, including pre–post-assessments of sleep difficulties, dysfunctional sleep beliefs, participation, and pain interference. Findings Indicators were supportive of feasibility, including reduced sleep difficulties (for example Medical Outcomes Study Sleep Measure [ t = 3.29, p = .02]), reduced nightmares: t = 2.79, p = .03; fewer dysfunctional sleep beliefs: t = 3.63, p = .01, and greater ability to participate in social roles: t = –2.86, p = .03, along with trends towards improved satisfaction with participation and reduced pain interference. Conclusion The Restoring Effective Sleep Tranquility program may reduce sleep difficulties and improve participation in US veterans with service-connected injuries, and evidence indicates a controlled trial would be feasible to deliver.
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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 | 0.014 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".