Examining the Pain Stages of Change Questionnaire in Chronic Pain
Bibliographic record
Abstract
Purpose: This study examined the relationships of a readiness to adopt a self-management approach to chronic pain, measured by the Pain Stages of Change Questionnaire (PSOCQ), with other pain-related scales in patients attending a chronic pain management program and determined if these measures changed from admission to discharge. The PSOCQ consists of four stages: Pre-contemplation, Contemplation, Action and Maintenance. Method: A convenience sample of 140 patients (mean age = 43.8 years; SD = 8.3 years) with chronic pain completed the PSOCQ, the Pain Disability Index (PDI), the Pain Intensity Scale (PIS), the Center for Epidemiologic Studies-Depression Scale (CES-D) and the Multidimensional Health Locus of Control Scale (MHLC) at admission and discharge. The MHLC consists of three subscales: Internal, Chance and Powerful Others. Results: At discharge, Pearson correlation coefficients demonstrated that Pre-contemplation was positively associated with the PDI, the PIS and the CES-D and negatively associated with Internal MHLC, whereas Action and Maintenance showed the opposite findings. There were significant improvements in all measures, except the MHLC, over the four-week program. Conclusions: These findings provide support for the use of the PSOCQ in assessing patients' readiness to adopt a self-management approach to pain and in monitoring their progress in rehabilitation.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".