The reliability and validity of the English version of the Evaluation of Daily Activity Questionnaire for people with rheumatoid arthritis
Bibliographic record
Abstract
OBJECTIVES: The Evaluation of Daily Activity Questionnaire (EDAQ) includes 138 items in 14 domains identified as important by people with RA. The aim of this study was to test the validity and reliability of the English EDAQ. METHODS: A total of 502 participants completed two questionnaires 3 weeks apart. The first consisted of the EDAQ, HAQ, RA Quality of Life (RAQoL) and the Medical Outcomes Scale (MOS) 36-item Short-Form Health Survey (SF-36v2), and the second consisted of the EDAQ only. The 14 EDAQ domains were tested for: unidimensionality-using confirmatory factor analysis; fit, response dependency, invariance across groups (differential item functioning)-using Rasch analysis; internal consistency [Person Separation Index (PSI)]; concurrent validity-by correlations with the HAQ, SF-36v2 and RAQoL; and test-retest reliability (Spearman's correlations). RESULTS: Confirmatory factor analysis of the 14 EDAQ domains indicated unidimensionality, after adjustment for local dependency in each domain. All domains achieved a root mean square error of approximation <0.10 and satisfied Rasch model expectations for local dependency. DIF by age, gender and employment status was largely absent. The PSI was consistent with individual use (PSI = 0.94 for all 14 domains). For all domains, except Caring, concurrent validity was good: HAQ (rs = 0.72-0.91), RAQoL (rs = 0.67-0.82) and SF36v2 Physical Function scale (rs = -0.60 to -0.84) and test-retest reliability was good (rs = 0.70-0.89). CONCLUSION: Analysis supported a 14-domain, two-component structure (Self care and Mobility) of the EDAQ, where each domain, and both components, satisfied Rasch model requirements, and have robust reliability and validity.
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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 | 0.011 | 0.022 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".