No Evidence for Depression Screening in Rheumatoid Arthritis, Psoriasis, or Psoriatic Arthritis
Bibliographic record
Abstract
To the Editor: Members of the Canadian Dermatology-Rheumatology Comorbidity Initiative recently recommended routine depression screening among patients with rheumatoid arthritis (RA), psoriasis (PsO), and psoriatic arthritis (PsA)1. Although this is described as an evidence-based recommendation, the only evidence that was presented was that patients with these conditions may have a higher prevalence of depression than people without chronic medical diseases and that 2 cohort studies have associated depression with a worse prognosis in RA. Depression screening involves administering self-report questionnaires or small sets of questions to identify patients who may have depression, but who are not already diagnosed or being treated for depression2. For a depression screening program to be successful, patients not already known to have depression must agree to be screened, a significant number of new cases must be identified with relatively few false-positive screens, and newly identified patients must engage in treatment with successful outcomes3. There are well-established criteria for evaluating when routine screening for any … Address correspondence to B.D. Thombs, Jewish General Hospital, 4333 Cote Ste Catherine Road, Montreal, Quebec H3T 1E4, Canada. E-mail: brett.thombs{at}mcgill.ca
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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 | 0.004 | 0.050 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.022 | 0.016 |
| Insufficient payload (model declined to judge) | 0.007 | 0.005 |
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".