Utility of the Brief Illness Perception Questionnaire to Monitor Patient Beliefs in Systemic Vasculitis
Bibliographic record
Abstract
Objective To assess the validity and clinical utility of the Brief Illness Perception Questionnaire (BIPQ) to measure illness perceptions in multiple forms of vasculitis. Methods Patients with giant cell arteritis (GCA), Takayasu arteritis (TA), antineutrophil cytoplasmic antibody–associated vasculitis (AAV), and relapsing polychondritis (RP) were recruited into a prospective, observational cohort. Patients independently completed the BIPQ, Multidimensional Fatigue Inventory (MFI), Medical Outcomes Study 36-item Short Form survey (SF-36), and a patient global assessment (PtGA) at successive study visits. Physicians concurrently completed a physician global assessment (PGA) form. Illness perceptions, as assessed by the BIPQ, were compared to responses from the full-length Revised Illness Perception Questionnaire (IPQ-R) and to other clinical outcome measures. Results There were 196 patients (GCA = 47, TA = 47, RP = 56, AAV = 46) evaluated over 454 visits. Illness perception scores in each domain were comparable between the BIPQ and IPQ-R (3.28 vs 3.47,P= 0.22). Illness perceptions differed by type of vasculitis, with the highest perceived psychological burden of disease in RP. The BIPQ was significantly associated with all other patient-reported outcome measures (rho = |0.50–0.70|,P< 0.0001), but did not correlate with PGA (rho = 0.13,P= 0.13). A change in the BIPQ composite score of ≥ 7 over successive visits was associated with concomitant change in the PtGA. Change in the MFI and BIPQ scores significantly correlated over time (rho = 0.38,P= 0.0008). Conclusion The BIPQ is an accurate and valid assessment tool to measure and monitor illness perceptions in patients with vasculitis. Use of the BIPQ as an outcome measure in clinical trials may provide complementary information to physician-based assessments.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".