Pilot study of a 4-week Pain Coping Strategies (PCS) programme for the chronic pain patient
Bibliographic record
Abstract
PURPOSE: A 4-week Pain Coping Strategies (PCS) programme has been developed for chronic pain patients who may still be undergoing medical interventions but who would benefit from learning pain management skills. The long-term negative behaviours associated with chronic pain may be prevented by introducing pain management strategies at an earlier stage. The PCS programme combines all the fundamental aspects of the traditional Pain Management Programme including exercise, relaxation, pacing, medication review, pain pathways, posture and challenging negative thoughts. METHOD: The study compared 31 patients' mood, functional status and physical ability pre and 6 weeks post the programme using the Hospital Anxiety and Depression Scale (HAD), Canadian Occupational Performance Measure (COPM) and a series of physical tests. A paired samples t-test showed a significant improvement in levels of depression and anxiety, functional status and physical ability. RESULTS: The results reveal that an early intervention programme may be effective for chronic pain patients by promoting self-management and teaching positive coping strategies. CONCLUSIONS: The current study has found promising results for a brief early intervention for chronic pain, regardless of completion of medical interventions.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".