Randomized Clinical Effectiveness Trial of Nurse-Administered Small-Group Cognitive Behavior Therapy for Persistent Insomnia in General Practice
Bibliographic record
Abstract
STUDY OBJECTIVES: Persistent insomnia, although very common in general practice, often proves problematic to manage. This study investigates the clinical effectiveness and the feasibility of applying cognitive behavior therapy (CBT) methods for insomnia in primary care. DESIGN: Pragmatic randomized controlled trial of CBT versus treatment as usual. SETTING: General medical practice. PARTICIPANTS: Two hundred one adults (mean age, 54 years) randomly assigned to receive CBT (n = 107; 72 women) or treatment as usual (n = 94; 65 women). INTERVENTION: CBT comprised 5 sessions delivered in small groups by primary care nurses. Treatment as usual comprised usual care from general practitioners. MEASUREMENTS AND RESULTS: Assessments were completed at baseline, after treatment, and at 6-month follow-up visits. Sleep outcomes were appraised by sleep diary, actigraphy, and clinical endpoint. CBT was associated with improvements in self-reported sleep latency, wakefulness after sleep onset, and sleep efficiency. Improvements were partly sustained at follow-up. Effect sizes were moderate for the index variable of sleep efficiency. Participants receiving treatment as usual did not improve. Actigraphically estimated sleep improved modestly after CBT, relative to no change in treatment as usual. CBT was also associated with significant positive changes in mental health and energy/vitality. Comorbid physical and mental health difficulties did not impair sleep improvement following CBT. CONCLUSION: This study suggests that trained and supervised nurses can effectively deliver CBT for insomnia in routine general medical practice. Treatment response to small-group service delivery was encouraging, although effect sizes were smaller than those obtained in efficacy studies. Further research is required to consider the possibility that CBT could become the treatment of first choice for persistent insomnia in primary healthcare.
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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 | 0.005 | 0.010 |
| 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 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 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".