Patients with rheumatoid arthritis facing sick leave or work disability meet varying regulations: a study among rheumatologists and patients from 44 European countries
Bibliographic record
Abstract
OBJECTIVES: To describe and explore differences in formal regulations around sick leave and work disability (WD) for patients with rheumatoid arthritis (RA), as well as perceptions by rheumatologists and patients on the system's performance, across European countries. METHODS: We conducted three cross-sectional surveys in 50 European countries: one on work (re-)integration and social security (SS) system arrangements in case of sick leave and long-term WD due to RA (one rheumatologist per country), and two among approximately 15 rheumatologists and 15 patients per country on perceptions regarding SS arrangements on work participation. Differences in regulations and perceptions were compared across categories defined by gross domestic product (GDP), type of social welfare regime, European Union (EU) membership and country RA WD rates. RESULTS: Forty-four (88%) countries provided data on regulations, 33 (75%) on perceptions of rheumatologists (n=539) and 34 (77%) on perceptions of patients (n=719). While large variation was observed across all regulations across countries, no relationship was found between most of regulations or income compensation and GDP, type of SS system or rates of WD. Regarding perceptions, rheumatologists in high GDP and EU-member countries felt less confident in their role in the decision process towards WD (β=-0.5 (95% CI -0.9 to -0.2) and β=-0.5 (95% CI -1.0 to -0.1), respectively). The Scandinavian and Bismarckian system scored best on patients' and rheumatologists' perceptions of regulations and system performance. CONCLUSIONS: There is large heterogeneity in rules and regulations of SS systems across Europe in relation to WD of patients with RA, and it cannot be explained by existing welfare regimes, EU membership or country's wealth.
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 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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".