Long-Term Efficacy of a Home-Care Hypnosis Program in Elderly Persons Suffering From Chronic Pain: A 12-Month Follow-Up
Bibliographic record
Abstract
BACKGROUND: Pain is a major public health concern in the aging population. However, medication brings about negative effects that compel healthcare professionals to seek alternative management techniques to alleviate pain. Hypnosis has been recognized as an effective technique to manage pain, but its long-term efficacy has yet to be examined in older adults. AIMS: The aim was to assess the effectiveness, over a 12-month period, of home-care hypnosis in elderly participants suffering from chronic pain. DESIGN: Real-life retrospective one-arm study with a 12-month follow-up. SETTINGS: Elderly Persons Suffering From Chronic Pain enrolled in a clinical health care program that offered home medical follow-up. PARTICIPANTS/SUBJECTS: Fourteen elderly women (mean age 81 years) with chronic pain participated in the home-care hypnosis program. All participants presented chronic pain (≥6 months) with average pain score >4/10. METHODS: Participants took part in seven 15-minute hypnosis sessions within 12 months. The Brief Pain Inventory questionnaire was used to evaluate pain perception and pain interference at baseline and at 3-, 6-, and 12-month follow-up period. RESULTS: Hypnosis home-care program significantly decreased pain perception and pain interference compared to baseline after 3 months (-29% and -40%, p < .001), and remained lower at 6 (-31% and -54%, p < .001) and 12 (-31% and -47%, p < .001) months. CONCLUSIONS: Seven sessions of 15 minutes allocated throughout a 12-month period produced clinically significant decreases in pain perception and pain interference. Hypnosis could be considered as an optimal additional way for health practitioners to manage chronic pain in an elderly population with long-term efficacy. This study offers a new long-term option to improve chronic pain management at home in elderly populations through a low-cost nonpharmacological intervention.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".