A Randomized Controlled Trial of Mindfulness Meditation for Chronic Insomnia
Bibliographic record
Abstract
STUDY OBJECTIVES: To evaluate the efficacy of mindfulness meditation for the treatment of chronic insomnia. DESIGN: Three-arm, single-site, randomized controlled trial. SETTING: Academic medical center. PARTICIPANTS: Fifty-four adults with chronic insomnia. INTERVENTIONS: Participants were randomized to either mindfulness-based stress reduction (MBSR), mindfulness-based therapy for insomnia (MBTI), or an eight-week self-monitoring (SM) condition. MEASUREMENTS AND RESULTS: Patient-reported outcome measures were total wake time (TWT) from sleep diaries, the pre-sleep arousal scale (PSAS), measuring a prominent waking correlate of insomnia, and the Insomnia Severity Index (ISI) to determine remission and response as clinical endpoints. Objective sleep measures were derived from laboratory polysomnography and wrist actigraphy. Linear mixed models showed that those receiving a meditation-based intervention (MBSR or MBTI) had significantly greater reductions on TWT minutes (43.75 vs 1.09), PSAS (7.13 vs 0.16), and ISI (4.56 vs 0.06) from baseline-to-post compared to SM. Post hoc analyses revealed that each intervention was superior to SM on each of the patient-reported measures, but no significant differences were found when comparing MBSR to MBTI from baseline-to-post. From baseline to 6-month follow-up, MBTI had greater reductions in ISI scores than MBSR (P < 0.05), with the largest difference occurring at the 3-month follow-up. Remission and response rates in MBTI and MBSR were sustained from post-treatment through follow-up, with MBTI showing the highest rates of treatment remission (50%) and response (78.6%) at the 6-month follow-up. CONCLUSIONS: Mindfulness meditation appears to be a viable treatment option for adults with chronic insomnia and could provide an alternative to traditional treatments for insomnia. TRIAL REGISTRATION: Mindfulness-Based Approaches to Insomnia: clinicaltrials.gov, identifier: NCT00768781.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 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".