Development of a Mixed Hypnosis and Music Intervention Program for the Management of Pain, Anxiety, and Wellbeing in End-of-Life Palliative Care
Bibliographic record
Abstract
Background: The palliative care people present needs that can be partially met by complementary intervention. Approaches based on the use of hypnosis and music are increasingly being studied and have shown potential benefits on pain, anxiety, and wellbeing for many populations including those in palliative care. Objective: This study aims to present the initial process of creating and refining a hypnosis and music intervention program intended for persons in palliative care, with a panel of experts of diverse relevant backgrounds. It also aims to evaluate its feasibility, preliminary acceptability, and content. Methods: To achieve the objectives, we followed ORBIT recommendations for the development and redesign of behavioral interventions (phase I a-b). Based on a meta-analysis, reference interventions were identified and then adapted to the target population. Twenty-two experts from different backgrounds were consulted to obtain their evaluation on the acceptability, feasibility, and content of the interventions. Result: The various components of the program were deemed appropriate or very appropriate by over 80% of the experts. However, possible risks were raised related to some uncertainty about the reactions of individuals to the intervention. Several experts (32%) indicated potential adverse effects consisting of negative emotional experiences during the sessions. Modifications were proposed specifically to reduce or mitigate this risk. Over 90% of the experts considered that the revised program provides a safer and more appropriate intervention for palliative care persons. Conclusion: A mixed intervention program with hypnosis and music has been developed and attained a high level of consensus by the experts. The proposed intervention is ready to be assessed for clinical efficacy in a pilot study (ORBIT Phase II).
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".