Translation and Cross-cultural Adaptation of the Lower Extremity Functional Scale Into a Brazilian Portuguese Version and Validation on Patients With Knee Injuries
Bibliographic record
Abstract
STUDY DESIGN: Clinical measurement. OBJECTIVE: To translate and culturally adapt the Lower Extremity Functional Scale (LEFS) into a Brazilian Portuguese version, and to test the construct and content validity and reliability of this version in patients with knee injuries. BACKGROUND: There is no Brazilian Portuguese version of an instrument to assess the function of the lower extremity after orthopaedic injury. METHODS: The translation of the original English version of the LEFS into a Brazilian Portuguese version was accomplished using standard guidelines and tested in 31 patients with knee injuries. Subsequently, 87 patients with a variety of knee disorders completed the Brazilian Portuguese LEFS, the Medical Outcomes Study 36-Item Short-Form Health Survey, the Western Ontario and McMaster Universities Osteoarthritis Index, and the International Knee Documentation Committee Subjective Knee Evaluation Form and a visual analog scale for pain. All patients were retested within 2 days to determine reliability of these measures. Validation was assessed by determining the level of association between the Brazilian Portuguese LEFS and the other outcome measures. Reliability was documented by calculating internal consistency, test-retest reliability, and standard error of measurement. RESULTS: The Brazilian Portuguese LEFS had a high level of association with the physical component of the Medical Outcomes Study 36-Item Short-Form Health Survey (r = 0.82), the Western Ontario and McMaster Universities Osteoarthritis Index (r = 0.87), the International Knee Documentation Committee Subjective Knee Evaluation Form (r = 0.82), and the pain visual analog scale (r = -0.60) (all, P<.05). The Brazilian Portuguese LEFS had a low level of association with the mental component of the Medical Outcomes Study 36-Item Short-Form Health Survey (r = 0.38, P<.05). The internal consistency (Cronbach α = .952) and test-retest reliability (intraclass correlation coefficient = 0.957) of the Brazilian Portuguese version of the LEFS were high. The standard error of measurement was low (3.6) and the agreement was considered high, demonstrated by the small differences between test and retest and the narrow limit of agreement, as observed in Bland-Altman and survival-agreement plots. CONCLUSION: The translation of the LEFS into a Brazilian Portuguese version was successful in preserving the semantic and measurement properties of the original version and was shown to be valid and reliable in a Brazilian population with knee injuries.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".