Polish Cross-Cultural Adaptation of the Lower Limb Functional Index (LLFI) Demonstrates a Valid Outcome Measure for the Lower Limb Region and Joints
Bibliographic record
Abstract
This study aimed to perform linguistic and cross-cultural adaptation to establish a Polish version of the Lower Limb Functional Index (LLFI) as well as an evaluation of the psychometric properties. This was a two-stage, cross-sectional study. The first stage—linguistic and cultural adaptation, complied with the International Society for Pharmacoeconomics and Outcomes Research guidelines to produce the Lower Limb Functional Index, Polish version (LLFI-PL). The subjects were recruited to the second stage of the study from a sample of convenience (n = 125, age x- = 52.86 ± 19.53 years, 56% female, symptoms duration x- = 17.69 ± 18.39 weeks). Baseline reliability was performed on the LLFI-PL with retest period at 3–7 days. The Western Ontario and McMaster University Osteoarthritis Index (WOMAC), EuroQol Health Questionnaire 5-Dimensions 5-Level (EQ-5D-5L), and an 11-point Pain Numerical Rating Scale (P-NRS) were completed to assess the validity of the LLFI-PL. Statistical analysis showed high internal consistency (α = 0.94), and excellent test–retest reliability (ICC2.1 = 0.96). The measurement error was SEM = 1.69% with MDC90 = 3.93%. Construct validity demonstrated strong correlations between the LLFI-PL and WOMAC (r = 0.81) and moderate correlations with the EQ-5D-5L (r = −0.63) and P-NRS (r = −0.39). Exploratory factor analysis confirmed a single-factor structure. The LLFI-PL is a psychometrically sound questionnaire for Polish-speaking patients with lower limb musculoskeletal conditions. The results support findings from the previous original English, Spanish, and Turkish versions.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".