Assessment of cross-cultural adaptations of patient-reported shoulder outcome measures in Spanish: a systematic review
Bibliographic record
Abstract
BACKGROUND: The present study aimed to conduct a systematic review of self-administered shoulder-disability functional assessment questionnaires adapted to Spanish, analyzing the quality of the transcultural adaptation and the clinimetric properties of the new version. METHODS: A search of the main biomedical databases was conducted to locate Spanish shoulder function assessment scales. The authors reviewed the papers and considered whether the process of adaptation of the questionnaire had followed international recommendations, and whether its psychometric properties had been appropriately assessed. RESULTS: The search identified nine shoulder function assessment scales adapted to Spanish: Disabilities of the Arm, Shoulder and Hand Questionnaire (DASH), Upper Limb Functional Index (ULFI), Simple Shoulder Test (SST), Shoulder Pain and Disability Index (SPADI), Oxford Shoulder Score (OSS), Shoulder Disability Questionnaire (SDQ), Western Ontario Rotator Cuff index (WORC), Western Ontario Shoulder Instability index (WOSI) and Wheelchair Users Shoulder Pain Index (WUSPI). The DASH was adapted on three occasions and the SPADI on two. The transcultural adaptation procedure was generally satisfactory, albeit somewhat less rigorous for the SDQ and WUSPI. Reliability was analyzed in all cases. Validity was not measured for one of the adaptations of the DASH, nor was it measured for the SDQ. CONCLUSIONS: The transcultural adaptation was satisfactory and the psychometric properties analyzed were similar to both the original version and other versions adapted to other languages.
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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 | 0.040 | 0.119 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.014 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".