Japanese cross-cultural validation study of the Pain Stage of Change Questionnaire
Bibliographic record
Abstract
INTRODUCTION: Although evidence supports efficacy of treatments that enhance self-management of chronic pain, the efficacy of these treatments has been hypothesized to be influenced by patient readiness for self-management. The Pain Stage of Change Questionnaire (PSOCQ) is a reliable and valid measure of patient readiness to self-manage pain. However, there is not yet a Japanese version of the PSOCQ (PSOCQ-J), which limits our ability to evaluate the role of readiness for pain self-management in function and treatment response in Japanese patients with chronic pain. OBJECTIVE: Here, we sought to develop the PSOCQ-J and evaluate its psychometric properties. METHODS: We recruited 201 patients with chronic pain. The study participants were asked to complete the PSOCQ-J and other measures assessing pain severity, pain interference, catastrophizing, self-efficacy, and pain coping strategies. RESULTS: The results supported a 4-factor structure of the PSOCQ-J. We also found good to excellent internal consistencies and good test-retest reliabilities for the 4 scales. The Precontemplation scale had weak to moderate positive correlations with measures of pain-related dysfunction and maladaptive coping. The Action and Maintenance scales had weak to moderate positive correlations with measures of self-efficacy and adaptive coping. The Contemplation scale had weak positive correlations with measures of pain interference and both adaptive and maladaptive coping. CONCLUSIONS: The PSOCQ-J demonstrated adequate psychometric properties in a sample of Japanese patients with chronic pain. This measure can be used to evaluate the role that readiness to self-manage pain may play in adjustment to chronic pain in Japanese pain populations.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".