Invalidation in Patients with Rheumatic Diseases: Clinical and Psychological Framework
Bibliographic record
Abstract
OBJECTIVE: The term "invalidation" refers to the patients' perception that their medical condition is not recognized by the social environment. Invalidation can be a major issue in patients' lives, adding a significant burden to symptoms and limitations while increasing the risk of physical and psychological disability. In this study in patients with rheumatic diseases, we investigated the relationship between invalidation and sociodemographic, clinical, psychological, and personality characteristics. METHODS: This international cross-sectional study included 562 adults with rheumatoid arthritis (n = 124), spondyloarthritis (n = 85), systemic lupus erythematosus (n = 112), or fibromyalgia (FM; n = 241). Assessed were the family and health professionals subscales of the Illness Invalidation Inventory (3*I), happiness (Subjective Happiness Scale), personality (Ten-Item Personality Inventory), pain, and loneliness (numerical rating scales). Univariate and multivariate analyses were used to test different models. RESULTS: Invalidation occurred in all rheumatic diseases, but patients with FM reported the most invalidation. Including all correlated variables in the multivariate model, pain remained as a determinant of invalidation by health professionals, but not by family. Regarding psychological variables, loneliness remained as a determinant of invalidation by family, but not by health professionals. FM and low levels of happiness, agreeableness, and conscientiousness were associated with invalidation while taking account of other variables. CONCLUSION: Invalidation occurs in all rheumatic diseases and patients with FM experience the most invalidation. Psychological factors (happiness, agreeableness, and conscientiousness), loneliness, and pain intensity are associated with invalidation, irrespective of the rheumatic disease and may deserve dedicated interventions.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".