Evaluation of Ankylosing Spondylitis Quality of Life (EASi-QoL): Reliability and Validity of a New Patient-reported Outcome Measure
Bibliographic record
Abstract
OBJECTIVE: There is currently no universally accepted measure of quality of life in ankylosing spondylitis (AS). Our objective was to develop and evaluate a patient-reported outcome measure of quality of life in AS, EASi-QoL. METHODS: We used patient interviews, a literature review, and completion of an individualized measure of AS quality of life during clinic-based and pilot surveys to derive questionnaire content. Classical and modern psychometrics were then used to evaluate the questionnaire using data from a large UK-based postal survey of 1000 patients with AS. RESULTS: Data analysis from the interviews and clinic-based and postal surveys produced a 57-item self-completed questionnaire. Fifteen items were removed as a result of patient interviews and the pilot survey. In total, 612 (64.0%) patients responded to the main postal survey. After assessment of data quality, confirmatory factor analysis, and Rasch analysis, 20 items were found to contribute to 4 domains of AS-related quality of life: physical function, disease activity, emotional well-being, and social participation. Item-total correlations ranged from 0.66 to 0.84. Cronbach's alpha and test-retest reliability estimates were 0.88-0.92 and 0.88-0.93, respectively. Confirmed hypothesized correlations with the AS Quality of Life questionnaire, the Bath AS Disease Activity Index, Bath AS Functional Index, SF-36, EQ-5D, and the Hospital Anxiety and Depression Scale were evidence for the construct validity of the EASi-QoL. CONCLUSION: The EASi-QoL has good evidence of data quality, internal reliability, test-retest reliability, and content and construct validity, and should be considered for use with patients in routine practice settings and in evaluative studies including clinical trials. Measurement responsiveness and minimal important change are currently being assessed.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| 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".