Cross-cultural adaptation and validation of the Spanish version of the Oxford Hip Score in patients with hip osteoarthritis
Bibliographic record
Abstract
BACKGROUND: Osteoarthritis (OA) of the hip is a disease that entails a major burden for patients and the society as a whole. One way of measuring this burden for the patient is through impact on Health-related Quality of Life (HRQL). The Oxford Hip Score (OHS) is a well-known tool to measure HRQL in patients with OA of the hip. This study aims to assess the psychometric properties of the Spanish-adapted version of the OHS, including its reliability, validity, and sensitivity to change. METHODS: Prospective observational study that included 361 patients diagnosed with hip OA (according to the criterion of the American College of Rheumatology) from 3 different Spanish regions. Their HRQL was assessed using a generic questionnaire, the EQ-5D-5 L, and two specific ones (the Western Ontario and McMaster Universities Osteoarthritis Index, WOMAC, and the OHS) adapted to Spanish. There was a follow-up period of 6 months, and the acceptability, psychometric properties, presence of ceiling and floor effects, validity, reliability, and sensitivity to changes of the OHS were measured. RESULTS: The OHS was fully answered in 99.4% of cases with no indication of ceiling or floor effects. Its factor structure can be explained in a single dimension. Its discriminative capacity was very good compared to the groups generated by the WOMAC and the EQ-5D-5 L. The correlation between the OHS and dimensions of the WOMAC or EQ-5D-5 L utilities was ≥0.7. Excellent test-retest reliability (ICC = 0.992; CI95%: 0.994-0.998) and internal consistency (Cronbach's α = 0.928) were observed. The minimal clinically important difference (MCID) was 7.0 points, and the minimum detectable change (MDC) was 5.5 points. The effect size for moderate improvement in perceived HRQL was 0.73, similar to that of WOMAC dimensions and higher than the EQ-5D-5 L. CONCLUSIONS: The Spanish-adapted version of the OHS is a useful, acceptable tool for the assessment of perceived HRQL in patients with hip OA, and has psychometric properties similar to those of the WOMAC that allow for discriminating both a patient's condition at a given moment and changes that can occur over time.
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 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 | 0.009 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".