Validation of the Danish translation of the illness intrusiveness rating scale in patients with rheumatic disease
Bibliographic record
Abstract
Rheumatic diseases significantly affects quality of life, making self-management critical. The Illness Intrusiveness Rating Scale (IIRS) measures the extent to which illness interferes with various life domains, but until now it has not been translated into Danish. This study aimed to translate the IIRS into Danish and assess its psychometric properties in Danish patients with a rheumatic disease. Following COSMIN guidelines, the IIRS was translated and culturally adapted through a multi-step process, including forward and backward translations and cognitive interviews. Psychometric testing included assessments of internal construct validity by confirmatory factor analysis, internal consistency by Cronbach’s α, reliability by test–retest, standard error of measurement, and responsiveness by minimal detectable change. The final Danish version was well-understood, though minor issues arose, such as the relevance of “religious expression.” The scale demonstrated high internal consistency (Cronbach’s α = 0.92). Confirmatory factor analysis confirmed the original three-factor structure with an acceptable model fit (comparative fit index = 0.94, the Root Mean Square Error of Approximation = 0.10). Strong correlations were found within “Relationships and Personal Development” and “Instrumental” domains, but the “Diet” item did not meet factor assignment criteria. Test–retest reliability was acceptable (intraclass correlation coefficients ≥ 0.70 for most items). The Danish IIRS showed strong psychometric properties, making it a reliable and valid tool for assessing illness impact and self-management interventions in Danish patients with rheumatic disease.
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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 | 0.016 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".