Practicing self-hypnosis to reduce chronic pain: A qualitative exploratory study of HYlaDO
Bibliographic record
Abstract
Background: Nearly a quarter of Canada’s population suffers from chronic pain, a long-lasting medical condition marked by physical pain and psychological suffering. Opioids are the primary treatment for pain management in this condition; yet, this approach involves several undesirable side effects. In contrast to this established approach, non-pharmacological interventions, such as medical hypnosis, represent an efficient alternative for pain management in the context of chronic pain. HYlaDO is a self-hypnosis program designed to improve pain management for people with chronic pain. Purpose: This research aimed to evaluate the HYlaDO program based on the proof-of-concept level of the ORBIT model and investigated participants’ subjective experience. Research design: Qualitative study. Study sample: Seventeen participants with chronic pain took part in this study. Data collection: We conducted individual semi-structured interviews with patients who had participated in HYlaDO to identify the three targets of desired change: pain, anxiety and autonomy in self-hypnosis practice. Results: Thematic analysis revealed that the practice of hetero-hypnosis and self-hypnosis decreased (i) pain and (ii) anxiety. Also, it (iii) indicated the development of an independent and beneficial self-hypnosis practice by having integrated the techniques taught. Conclusion: These results confirm that the established targets were reached and support further development, implementation and scaling up of this program. Consequently, we believe it is justified to move to the next step of program development.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.054 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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; both teacher heads agree on what is shown here.
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".