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Internal Structure and Validity of the Multidimensional Pain Inventory, Italian Language Version

2000· article· en· W2031173122 on OpenAlexaboutno aff
Renata Ferrari, Caterina Novara, Ezio Sanavio, Federica Zerbini

Bibliographic record

VenuePain Medicine · 2000
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsnot available
Fundersnot available
KeywordsCronbach's alphaBeck Depression InventoryConfirmatory factor analysisReliability (semiconductor)Clinical psychologyPsychologyPsychometricsConstruct validityAnxietyConvergent validityCephalalgiaConcurrent validityPhysical therapyInternal consistencyMedicinePsychiatryComputer scienceStructural equation modeling

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.368
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.008
GPT teacher head0.264
Teacher spread0.256 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations24
Published2000
Admission routes1
Has abstractyes

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