Health-related quality of life in ANCA-associated vasculitis and item generation for a disease-specific patient-reported outcome measure
Bibliographic record
Abstract
OBJECTIVE: The antineutrophil cytoplasmic antibody (ANCA)-associated vasculitides (AAVs) are multisystem diseases of the small blood vessels. Patients experience irreversible damage and psychological effects from AAV and its treatment. An international collaboration was created to investigate the impact of AAV on health-related quality of life (HRQoL), and develop a disease-specific patient-reported outcome measure to assess outcomes of importance to patients. METHODS: Patients with AAV from the UK, USA, and Canada were interviewed to identify salient aspects of HRQoL affected by AAV. The study was overseen by a steering committee including four patient research partners. Purposive sampling of interviewees ensured representation of a range of disease manifestations and demographics. Inductive analysis was used to identify themes of importance to patients; these were further confirmed by a free-listing exercise in the US. Individual themes were recast into candidate items, which were scrutinized by patients, piloted through cognitive interviews and received a linguistic and translatability evaluation. RESULTS: Fifty interviews, conducted to saturation, with patients from the UK, USA, and Canada, identified 55 individual themes of interest within seven broad domains: general health perceptions, impact on function, psychological perceptions, social perceptions, social contact, social role, and symptoms. Individual themes were constructed into >100 candidate questionnaire items, which were then reduced and refined to 35 candidate items. CONCLUSION: This is the largest international qualitative analysis of HRQoL in AAV to date, and the results have underpinned the development of 35 candidate items for a disease-specific, patient-reported outcome questionnaire.
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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 | 0.013 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".