Internal Structure and Validity of the Multidimensional Pain Inventory, Italian Language Version
Bibliographic record
Abstract
OBJECTIVE: The aim of the study is an investigation of the psychometric characteristics of the Italian translation of the Multidimensional Pain Inventory and a comparison with the American, German, Swedish and Dutch versions of the MPI. METHOD: The Italian translation of the MPI was administered together with Melzack McGill Pain Inventory, Beck Depression Inventory, Spielberger State-Trait Anxiety Inventory, and Visual Analog Scales. Confirmatory factor analyses were accomplished on the MPI scores. Furthermore, reliability, intercorrelations, and convergent validity of MPI were evaluated. PATIENTS: Participants were 220 patients suffering from a variety of chronic pain syndromes (cephalalgia 45.8%; low-back pain 30.5%). RESULTS: Confirmatory factor analyses suggest changes to all 3 sections of the MPI-IV. Factor structure, after having excluded several items sorted according to the 3 sections of the questionnaire, is basically the same as in other versions of the MPI. Internal consistency analyses yielded acceptable reliability (Cronbach alpha coefficients) for 11 out of 13 scales. CONCLUSIONS: After making appropriate changes in all 3 sections of the inventory, the MPI is substantially suitable for use in cross-cultural and international research.
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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 | 0.005 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".