Validity and reliability of the Arabic version of the patient's joint perception question in patients undergoing knee arthroplasty
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Purpose Total knee arthroplasty (TKA) aims to alleviate pain and restore function in patients with knee osteoarthritis. While the Forgotten Joint Score (FJS) and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) are established measures of patient satisfaction and functional outcomes after TKA, they may not directly capture the patient's subjective perception of the joint itself. The FJS was used to assess concurrent validity, as it reflects the degree to which patients are unaware of their artificial joint, which is related to joint perception. The patient's joint perception (PJP) question offers a simplified alternative to evaluate joint awareness. Methods This prospective observational study included patients who underwent TKA between 2018 and 2023. An Arabic version of the PJP (Ar‐PJP) question was translated using a forward‐backwards translation process. Participants completed the PJP, FJS, and reduced WOMAC at two time points, three weeks apart. Statistical analyses assessed validity and reliability using Pearson's correlation coefficient. Results A total of 100 participants were included in the study. The mean PJP score was 28.9 (standard deviation [SD]: 13.7), and the mean WOMAC score was 46.1 (SD: 17.8). A moderate negative correlation was found between the Ar‐PJP score and FJS ( r = −0.683; p < 0.001), A moderate negative correlation was found between the Ar‐PJP score and FJS ( r = −0.683; p < 0.001), while the correlation with WOMAC was weak and non‐significant ( r = −0.088; p = 0.382), supporting discriminant validity. Conclusions The Ar‐PJP is a valid and reliable tool for assessing patients' perceptions post‐TKA. As a single‐question measure, it simplifies evaluations and enhances patient care in Arabic‐speaking populations. Level of Evidence Level II.
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Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
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 | 0.001 |
| 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 it