Appraisal of Candidate Instruments for Assessment of the Physical Function Domain in Patients with Psoriatic Arthritis
Bibliographic record
Abstract
OBJECTIVE: Numerous patient-reported outcome measures (PROM) exist for the measurement of physical function for psoriatic arthritis (PsA), but only a few are validated comprehensively. The objective of this project was to prioritize PROM for measuring physical function for potential incorporation into a standardized outcome measurement set for PsA. METHODS: A working group of 13 members including 2 patient research partners was formed. PROM measuring physical function in PsA were identified through a systematic literature review and recommendations by the working group. The rationale for inclusion and exclusion from the original list of existing PROM was thoroughly discussed and 2 rounds of Delphi exercises were conducted to achieve consensus. RESULTS: Twelve PROM were reviewed and discussed. Six PROM were prioritized: Health Assessment Questionnaire (HAQ) and 4 modifications (HAQ-Disability Index, HAQ-Spondyloarthritis, modified HAQ, multidimensional HAQ), Medical Outcomes Study 36-item Short Form survey physical functioning domain, and the Patient-Reported Outcomes Measurement Information System (PROMIS) physical functioning module. CONCLUSION: Through discussion and Delphi exercises, we achieved consensus to prioritize 6 physical function PROM for PsA. These 6 PROM will undergo further appraisal using the Outcome Measures in Rheumatology (OMERACT) Filter 2.1.
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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 | 0.033 | 0.057 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".