Hypnosis Program Effectiveness in a 12-week Home Care Intervention To Manage Chronic Pain in Elderly Women: A Pilot Trial
Bibliographic record
Abstract
PURPOSE: As the prevalence of pain increases with age, taking too much medication can lead to negative side effects in elderly patients. While evidence in the literature has shown that clinical hypnosis is effective in an adult population, there are few studies in an aging population and efficacy has never been established in a home care setting. The goal of this study was to determine the effects of a hypnosis program delivered during home care interventions in elderly women during a 12-week period. METHODS: This pilot trial took place from April 2016 to October 2017 at Limoges, France. Fifteen elderly women with chronic pain participated (81 (65-87) years old). All participants presented chronic pain for more than 6 months (inclusion criteria: average pain score >4/10). Participants took part in three 15-min hypnosis sessions separated by four to six weeks. Each hypnosis session was personalized and carried out with induction, pain perception alteration, and post-hypnotic suggestions. Pain perception and pain interference were evaluated with the Brief Pain Inventory questionnaire, and compared between before and after the 12-week hypnosis program. FINDINGS: Hypnosis home care program significantly improved scores on worst (8.9 to 6.7, P < 0.001), average (6.8 to 5.1, P < 0.001), and current pain perception (6.5 to 3.9, P < 0.001), pain interference with physical activity (P < 0.001) and with socio-affective factors (P < 0.01). IMPLICATIONS: Taken together, these findings show that a hypnosis intervention is feasible and effective to manage pain in an elderly population.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".