Nonpharmacologic group treatment of insomnia: a preliminary study with cancer survivors
Bibliographic record
Abstract
This study describes, and examines the initial efficacy of, a sleep therapy programme developed for cancer patients with insomnia. The six-session group programme included stimulus control therapy, relaxation training, and other strategies aimed at consolidating sleep and reducing cognitive-emotional arousal. The 12 final participants were patients of a regional cancer centre; mean age was 54.7 years (S.D. 10.4); median time from cancer diagnosis was 33.6 months; all had high performance status. Participants kept sleep diaries and rated their sleep quality, mood and functioning at baseline, week 4 and week 8. Significant improvement over baseline was observed at weeks 4 and 8 in the number of awakenings, time awake after sleep onset, sleep efficiency, sleep quality ratings, and scores on European Organization for Research and Treatment of Cancer (EORTC) QLQ-C30 role functioning and insomnia. Total sleep time and fatigue were significantly improved at week 8. The sleep therapy programme was associated with improved sleep, reduced fatigue and enhanced ability to perform activities in relatively well individuals attending a cancer centre. This is preliminary evidence of the efficacy of the programme. Further research is required to examine the programme's effectiveness and suitability for a wider range of people with cancer. Options for providing cancer patients with access to nonpharmacologic treatments for insomnia are discussed.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".