Construct Validity and Reliability of the Disability ofArm, Shoulder and Hand Questionnaire for Upper Extremity Complaints in Rheumatoid Arthritis
Bibliographic record
Abstract
OBJECTIVE: The Disability of Arm, Shoulder and Hand (DASH) questionnaire is a tool for measuring physical function and symptoms of the upper extremity. Although widely used, it is not validated for rheumatoid arthritis (RA). In this study the DASH was validated for this patient group. METHODS: In total, 102 patients participated in this study. For the validation, the questionnaires of the DASH, the Health Assessment Questionnaire (HAQ), the Medical Outcomes Study Short Form-36 (SF-36), and the Arthritis Impact Measurement Scale (AIMS2) were used. Patients were examined clinically before completing the questionnaires. Pain was scored by each patient using a visual analog scale (VAS). The Disease Activity Score (DAS28) was obtained and grip strength was measured. Reliability was tested by a second DASH questionnaire after 2 days. Validity was tested using a Pearson correlation analysis for the relevant domains of the questionnaires and for the clinical aspects. RESULTS: The reliability of the DASH was excellent (intraclass correlation coefficient 0.97). Internal consistency was strong (Cronbach's alpha 0.97). Validity was proven with excellent results for Pearson correlation with the relevant domains of the questionnaires: HAQ, r = 0.88; SF-36, r = 0.70; and AIMS2, r = 0.85. The clinical scores had a relatively low correlation with the DASH (DAS28, r = 0.42; and grip strength, r = 0.41-0.48), except for the VAS (r = 0.60-0.65). CONCLUSION: The DASH is a reliable and valid questionnaire in patients with RA. It can be used as a measurement tool of physical disability of the upper extremity.
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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 | 0.016 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".