Hypnosis and music interventions for anxiety, pain, sleep and well-being in palliative care: systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Maintaining quality of life is a primary goal of palliative care (PC). Complementary interventions can help meet the needs of patients at the end of life. OBJECTIVES: This meta-analysis aims to (1) evaluate the feasibility, acceptability and fidelity of music and hypnosis interventions designed for patients in PC and (2) evaluate the impact of these interventions on pain, anxiety, sleep and well-being. METHODS: Relevant studies were sourced from major databases. We selected both randomised controlled trials (RCTs) and studies relying on pre-post design with details of the intervention(s). RESULTS: Four RCT and seven non-randomised pre-post studies met the inclusion criteria. Overall, the feasibility and acceptability of the interventions reached an adequate level of satisfaction. However, only three studies reported using a written protocol. The meta-analysis of RCT indicated a significant decrease in pain with an effect size of -0.42, p=0.003. The small number of RCT studies did not allow us to quantify the effects for other variables. Analyses of data from pre-post designs indicated a favourable outcome for pain, anxiety, sleep and well-being. CONCLUSION: Despite the limited number of studies included in our meta-analysis, hypnosis and music intervention in the context of PC shows promising results in terms of feasibility and acceptability, as well as improvements on pain, anxiety, sleep and well-being. The available studies are insufficient to compare the efficacy across interventions and assess the potential benefits of their combinations. These results underscore the importance of further research on well-described complementary interventions relying on hypnosis and music. PROSPERO REGISTRATION NUMBER: CRD-42021236610.
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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 | 0.011 | 0.027 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.021 | 0.035 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".