Systematic Review of the Prevalence, Predictors, and Treatment of Insomnia in Palliative Care
Bibliographic record
Abstract
INTRODUCTION: The primary function of palliative care is to improve quality of life. The recognition and treatment of symptoms causing suffering is central to the achievement of this goal. Insomnia reduces quality of life of patients under palliative care. Knowledge about prevalence, associated factors, and treatment of insomnia in palliative care is scarce. METHODOLOGY: Literature review about the prevalence, predictors, and treatment options of insomnia in palliative care patients. Primary sources of investigation were identified and selected through Pubmed and Scopus databases. The research was complemented by reference search in identified articles and selected reviews. OpenGrey and Google Scholar were used for searching grey literature. Study quality analysis was based on the Newcastle-Ottawa Scale. RESULTS: A total of 65 studies were included in the review. Most studies had acceptable /good quality. The prevalence of insomnia in the included studies ranged from 2.1% to 100%, with a median overall prevalence of 49.5%. Sociodemographic factors such as age; clinical characteristics such as functional status, disease stage, pain, and use of specific drugs, including opioids; psychological factors such as anxiety/depression; and spiritual factors such as feelings of well-being were identified as predictors. The treatment options identified were biological (pharmacological and nonpharmacological), psychological (visualization, relaxation), and spiritual (prayer). CONCLUSIONS: The systematic review showed that the prevalence of insomnia is high, with at least one in 3 patients affected in most studies. Insomnia's risk factors and treatment in palliative care are both associated to physical, psychological, social, and spiritual factors, reflecting its true holistic nature.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".