Which aspects of health are most important for patients with spondyloarthritis? A Best Worst Scaling based on the ASAS Health Index
Bibliographic record
Abstract
OBJECTIVE: The aim was to investigate the importance of aspects of health for patients with axial SpA (axSpA) and to explore differences across different subgroups. METHODS: A Best Worst Scaling exercise was conducted in patients with axSpA from 20 countries (10 patients per country) worldwide. Using the 17 items of the Assessment of SpondyloArthritis international Society Health Index, a set of 17 choice tasks was generated. Patients had to indicate in each choice task the most and least important out of four varying items. The hierarchical Bayes method was used to estimate the relative importance score for each item (summing to 100). Subgroup comparisons were performed for relevant demographic (gender, age, work status, geographical area and education) and disease characteristics (SpA phenotype, disease duration and disease activity) using one-way analysis of variance or the Mann-Whitney U-test. RESULTS: The experiment was completed by 199 patients with axSpA [117 (58.8%) men, mean (sd) age 42.3 (13.6) years, mean (sd) disease duration 11.1 (11.2) years, 130 (65.3%) AS]. The highest relative importance was assigned to pain (14.2; 95% CI: 13.8, 14.6), sleep (10.3; 95% CI: 9.6, 11.0), being exhausted (9.6; 95% CI: 9.0, 10.3), standing (9.25; 95% CI: 8.5, 10.0) and motivation to do anything that requires physical effort (8.7; 95% CI: 8.1, 9.3). The lowest relative importance was assigned to sexual relationships, toileting, contact with people, driving and washing hair. Differences between subgroups were small or in aspects with lower importance. CONCLUSION: A clear gradient was seen in the importance of the different aspects of health that impact functioning of patients with axSpA. Differences between subgroups were small or non-existent. These findings help to align clinical care to patients' needs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".