Cross-cultural Adaptation and Psychometric Evaluation of the Persian Version of the Satisfaction and Recovery Index (SRI): Structural Validity, Construct Validity, Internal Consistency, and Test-retest Reliability.
Bibliographic record
Abstract
Background: The Satisfaction and Recovery Index (SRI) is a generic importance-weighted health satisfaction tool to measure the process and state of recovery following musculoskeletal injuries. The objectives of this study are (1) to translate and cross-culturally adapt the SRI to Persian and (2) evaluate its psychometric properties. Methods: The forward-backward translation technique was used for translation, and two rounds of cognitive interviews were conducted to assess cultural appropriateness. Participants (n=100, mean age=32.5, 82%male) had acute (i.e., <30 days) musculoskeletal injuries of any etiology. Structural validity, construct validity, internal consistency, and test-retest reliability were evaluated. Results: =0.72). Conclusion: The psychometric evaluation revealed that the SRI-P has adequate construct validity, internal consistency, and test-retest reliability. Unlike the original English version, the SRI-P has a two-factor structure, which appears to be related to cultural differences in interpreting some of the items. The clinical importance of this study is that the SRI (which captures the state of recovery and how important the various items of the tool are to each patient and how satisfied they are with their recovery) can now be available to surgeons and therapists in the orthopedic and rehabilitation realms in Persian populations.
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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 | 0.009 | 0.017 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".