Insomnia as an Unmet Need in Patients With Chronic Hematological Cancer: Protocol for a Randomized Controlled Trial Evaluating a Consumer-Based Meditation App for Treatment of Sleep Disturbance
Bibliographic record
Abstract
BACKGROUND: To address the need for long-term, accessible, nonpharmacologic interventions targeting sleep in patients with chronic hematological cancer, we propose the first randomized controlled trial to determine the effects of a consumer-based mobile meditation app, Calm, on sleep disturbance in this population. OBJECTIVE: This study aims to test the efficacy of daily meditation delivered via Calm compared with a health education podcast control group in improving the primary outcome of self-reported sleep disturbance, as well as secondary sleep outcomes, including sleep impairment and sleep efficiency; test the efficacy of daily meditation delivered via Calm compared with a health education podcast control group on inflammatory markers, fatigue, and emotional distress; and explore free-living use during a 12-week follow-up period and the sustained effects of Calm in patients with chronic hematological cancer. METHODS: In a double-blinded randomized controlled trial, we will recruit 276 patients with chronic hematological cancer to an 8-week app-based wellness intervention-the active, daily, app-based meditation intervention or the health education podcast app control group, followed by a 12-week follow-up period. Participants will be asked to use their assigned app for at least 10 minutes per day during the 8-week intervention period; complete web-based surveys assessing self-reported sleep disturbance, fatigue, and emotional distress at baseline, 8 weeks, and 20 weeks; complete sleep diaries and wear an actigraphy device during the 8-week intervention period and at 20 weeks; and complete blood draws to assess inflammatory markers (tumor necrosis factor-α, interleukin-6, interleukin-8, and C-reactive protein) at baseline, 8 weeks, and 20 weeks. RESULTS: This project was funded by the National Institutes of Health National Cancer Institute (R01CA262041). The projects began in April 2022, and study recruitment is scheduled to begin in October 2022, with a total project duration of 5 years. We anticipate that we will be able to achieve our enrollment goal of 276 patients with chronic hematological cancers within the allotted project time frame. CONCLUSIONS: This research will contribute to broader public health efforts by providing researchers and clinicians with an evidence-based commercial product to improve sleep in the long term in an underserved and understudied cancer population with a high incidence of sleep disturbance. TRIAL REGISTRATION: ClinicalTrials.gov NCT05294991; https://clinicaltrials.gov/ct2/show/NCT05294991. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/39007.
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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 | 0.027 | 0.022 |
| Meta-epidemiology (narrow) | 0.006 | 0.003 |
| Meta-epidemiology (broad) | 0.011 | 0.007 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.048 | 0.007 |
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".