Validación del índice de Lattinen para la evaluación del paciente con dolor crónico
Bibliographic record
Abstract
Background and objectives: the Lattinen Index (LI) is a widely used tool for pain assessment in Spanish speaking countries, both in clinical practice and research. Nevertheless, despite its extensive use, no validation of the Spanish language version of the questionnaire has been published yet. This study intends to validate LI as a tool for measuring chronic pain. Materials and methods: a multicentre, cross-sectional, non-interventional study, including 283 chronic pain patients (> 3 months duration), from 6 different centres, was performed. Validity and reliability analysis were performed in order to validate the IL. On a first visit patients completed the IL questionnaire and other conventional pain scales (Visual Analogic Scale [VAS], McGill Pain Questionnaire and three Likert scales evaluating Analgesic Consumption, Functional Ability, and Hours of Sleep), which acted as gold standards validity measurements. A sub-set of 83 patients, with stable clinical characteristics, was asked to retake the initial tests after 15 days, to measure test-retest reliability. Results: a statistically significant positive correlation was found between the total IL score and the degree of pain measured by VAS. The measurements from the individual items in the questionnaire: Pain intensity, Pain frequency, Analgesic consumption, Functional Ability and Hours of Sleep correlated from moderately to strongly, with the respective gold standards measurements. Internal consistency and test-retest assays showed coefficient values of: alpha > 0.7 and intraclass correlation > 0.85, respectively. Conclusions: IL validity was established both for the overall score as for the individual dimensions, proving a correlation with standard measurements. Reliability of IL was demonstrated with the results from internal consistency and test-retest analysis, which indicated a high homogeneity between items.
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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 | 0.010 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".