Screening for Anxiety in Patients With Inflammatory Arthritis Using the Multidimensional Health Assessment Questionnaire
Bibliographic record
Abstract
OBJECTIVE: To analyze the Multidimensional Health Assessment Questionnaire (MDHAQ) in screening for anxiety in patients with rheumatoid arthritis (RA) and psoriatic arthritis (PsA), compared to the Hospital Anxiety and Depression Scale (HADS) as the reference standard. METHODS: Patients with a physician diagnosis of RA or PsA were invited to complete the MDHAQ and HADS at their routine rheumatology clinic visit. Sensitivity, specificity, percent agreement, and [Formula: see text] statistics were used to evaluate agreement between 2 MDHAQ items for anxiety and HADS subscale for Anxiety (HADS-A) score of ≥ 8. The first item is a question asked on a 4-point scale (0-3.3), and the second is a yes or no (blank) question asked within a 60-item review of symptoms (ROS) checklist. RESULTS: The study included 183 participants, of whom 126 (68.9%) had RA and 57 (31.1%) had PsA. The mean age was 57.3 years and 66.7% were female. Positive screening for anxiety according to a HADS-A score of ≥ 8 was seen in 39.3% of patients. Compared to those with a HADS-A score of ≥ 8, patients with an MDHAQ score of ≥ 2.2 or a positive on ROS had a sensitivity of 69.9%, specificity of 73.6% and substantial agreement (agreement 80.9%, [Formula: see text] 0.59). CONCLUSION: The MDHAQ provides information similar to the HADS in screening for anxiety in patients with RA and PsA. The use of this single questionnaire, which can also be used to monitor clinical status and to screen for fibromyalgia and depression without requiring multiple questionnaires, may prove a valuable tool in routine clinical practice.
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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 | 0.002 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".