Perceptions of Patients, Caregivers, and Healthcare Providers of Idiopathic Inflammatory Myopathies: An International OMERACT Study
Bibliographic record
Abstract
OBJECTIVE: Patient-reported outcome measures (PROM) that incorporate the patient perspective have not been well established in idiopathic inflammatory myopathies (IIM). As part of our goal to develop IIM-specific PROM, the Outcome Measures in Rheumatology (OMERACT) Myositis special interest group sought to determine which aspects of disease and its effects are important to patients and healthcare providers (HCP). METHODS: Based on a prior qualitative content analysis of focus groups, an initial list of 24 candidate domains was constructed. We subsequently conducted an international survey to identify the importance of each of the 24 domains to be assessed in clinical research. Patients with IIM, their caregivers, and HCP treating IIM completed the survey. RESULTS: In this survey, a total of 638 respondents completed the survey, consisting of 510 patients, 101 HCP, and 27 caregivers from 48 countries. Overall, patients were more likely to rank "fatigue," "cognitive impact," and "difficulty sleeping" higher compared with HCP, who ranked "joint symptoms," "lung symptoms," and "dysphagia" higher. Both patients and providers rated muscle symptoms as their top domain. In general, patients from different countries were in agreement on which domains were most important. One notable exception was that patients from Sweden and the Netherlands ranked lung symptoms significantly higher compared to other countries including the United States and Australia (mean weighted rankings of 2.86 and 2.04 vs 0.76 and 0.80, respectively; p < 0.0001). CONCLUSION: Substantial differences exist in how IIM is perceived by patients compared to HCP, with different domains prioritized. In contrast, patients' ratings across the world were largely similar.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.001 |
| 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".