The effectiveness of hypnotherapy in the treatment of anxiety in patients with cancer receiving palliative care
Bibliographic record
Abstract
Introduction In palliative care patients, anxiety is usually attributed to a reaction to diagnosis, treatment and its possible outcomes. Despite the support for hypnotherapy as a resource for the alleviation of psychological and emotional distress, there is a paucity of evidences to support the use of hypnotherapy for symptom relief. Aims Aims of this study were to assess the benefits of hypnotherapy in the management of anxiety in palliative care patients and to ascertain if hypnotherapy could affect other symptoms including depression and sleep disturbance. Methods Participants received four sessions of hypnotherapy and completed the Hospital Anxiety and Depression Scale, Edmonton Symptom Assessment Scale, Verran and Snyder-Halpern Scale, and wrist actigraphy. Out of 21 patients recruited, eleven successfully completed the study. Results After the second hypnotherapy session there was a statistically significant reduction in patient-reported anxiety (p=0.0066) and symptoms (p=0.0094), but not in depression (p=0.2910) or sleep disturbance (p=0.0868). After the fourth hypnotherapy session, there was a statistically significant reduction in patient-reported anxiety (p=0.0016), depression (p=0.0466), symptoms (p=0.0329) and sleep disturbance (p=0.0081). Actigraphy did not show a statistically significant improvement in sleep quality. Discussion Hypnotherapy intervention appears to have a more immediate impact on anxiety and symptom severity whereas the improvement in depression and sleep quality is more slowly acquired. Actigraphy is a new tool to measure the quality of sleep. Its validation is still in progress and thus the sleep indicators chosen for this study are still a subject of debate. This could explain the result inconsistency. Conclusion This study suggests that hypnotherapy can contribute to reduction in anxiety in palliative care patients with the added benefit of improving sleep and severity of psychological and physical symptoms.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".