Integrative Approaches for Sleep Health in Cancer Survivors
Bibliographic record
Abstract
Sleep disturbance and insomnia are prevalent problems for the more than 15 million cancer survivors in the United States. If not addressed, poor-quality sleep can negatively impact physical and psychological recovery from cancer diagnosis and treatment. Cancer survivors are increasingly turning to integrative therapies to improve sleep and optimize their health. The purpose of this article is to review the evidence for the use of nonpharmacological integrative therapies to improve sleep health in cancer patients. Therapies are grouped into the following categories: cognitive-behavioral, meditative (e.g., mindfulness-based interventions, yoga, qigong/tai chi), and body based (e.g., acupuncture, acupressure, massage, reflexology). Cognitive-behavioral therapy for insomnia, mindfulness-based therapies, qigong/tai chi, and acupuncture have the most evidence for improving sleep and insomnia, whereas yoga, acupressure, massage, and reflexology are still being investigated or building their evidence base. Several areas of strength are identified, gaps in the literature are highlighted, and recommendations for improving future research are provided.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".