Validation of the Japanese Version of the Pain Self-Efficacy Questionnaire in Japanese Patients with Chronic Pain
Bibliographic record
Abstract
OBJECTIVES: The present study aimed to develop the Japanese version of the Pain Self-Efficacy Questionnaire (PSEQ-J) and to evaluate its psychometric properties. DESIGN: Cross-sectional design. SETTING: A pain clinic, a neurosurgery unit, and an orthopedic surgery unit in one university hospital and a pain clinic in a municipal hospital. METHODS: One hundred and seventy-six participants completed study measures, which included 1) the PSEQ-J, 2) the Hospital Anxiety and Depression Scale, 3) the Pain Catastrophizing Scale, 4) the Medical Outcome Study Short-Form 36, 5) the Pain Disability Assessment Scale, and 6) the Short-Form McGill Pain Questionnaire. RESULTS: The PSEQ-J demonstrated adequate reliability and validity. Hierarchical multiple regression analyses showed that pain self-efficacy as measured with the PSEQ-J accounted for a significant proportion of the variance on the measures administered in the present study. The PSEQ-J was most strongly associated with social activity. CONCLUSIONS: The results demonstrated that the PSEQ-J has adequate psychometric properties, supporting its use in clinical and research settings and suggest that the PSEQ-J may be particularly strongly associated with more social and less physical activity.
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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 | 0.006 | 0.011 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".