Total Hip Arthroplasty: Psychometric Validation of the Italian Version of Forgotten Joint Score (FJS-12)
Bibliographic record
Abstract
Abstract Background: Patient’s satisfaction after surgery was traditionally assessed by pre, and post-surgical scores and Patient-Reported Outcome Measures (PROMs) scales. Patients treated by Total hip arthroplasty (THA) usually perform well; therefore, it is useful to have a PROMs’ scale with a low ceiling effect as the Forgotten Joint Score-12 (FJS-12). PROMs have to be validated in the local language to be used. This study aims to perform a psychometric validation of the Italian version of FJS-12 in a group of consecutive patients treated by THA.Methods: Each patient completed both the Italian version of FJS-12 and Western Ontario and McMaster University Osteoarthritis Index (WOMAC) in preoperative evaluation, after two weeks and 1 month, 3 months and 6 months postoperative follow-up. The reliability, internal consistency, test-retest reliability, and measurement error were evaluated.Results: 53 patients were included. Cronbach’s α between 0.6 and 0.9 indicated good internal consistency for the FJS-12. The test-retest reliability was acceptable. The Pearson correlation coefficient between the FJS-12 and WOMAC was 0.238 (P=0.087) at baseline, r = 0.637 (P < 0.001) at 1 month, r = 0.490 (P < 0.001) at 3 months and r = 0.572 (P < 0.001) at 6 months. The ceiling effect was above the acceptable range (15%) for FJS-12 in 1 month (26.4%) and WOMAC in 6 months follow-up (24.5%).Conclusions: An excellent test-retest reliability, a good internal consistency, and a good validity by medium-high correlation with the WOMAC were assessed for FJS-12. However, the responsiveness for the FJS-12 score was not assessed.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".