The Myositis Activities Profile — Initial Validation for Assessment of Polymyositis/Dermatomyositis in the USA
Bibliographic record
Abstract
OBJECTIVE: To evaluate some measurement properties of the Myositis Activities Profile (MAP) in adult patients with polymyositis (PM) and dermatomyositis (DM) in the United States. METHODS: To assess content validity, patients with PM/DM rated difficulty and importance of items of the MAP using a visual analog scale (VAS), range 0-10. For construct validity, consecutive patients with PM/DM performed the 6-item core set for disease activity including the manual muscle test (MMT) and the Health Assessment Questionnaire (HAQ), the Functional Index-2 (FI-2; muscle endurance), and the MAP plus disease effect on well-being on a VAS. Item fit within subscales was analyzed by Cronbach's alpha. Patients with stable disease activity filled out the MAP again 1 week later. RESULTS: The median combined difficulty and importance, 0-10, of the 31 items was 5.00 (range 2.10-5.95). One item was added, giving a 32-item MAP. Correlations between the median of subscales/single items of the MAP and the HAQ and disease effect on well-being were r(s) = 0.69 and r(s) = 0.68, respectively, with lower correlations to the MMT (r(s) = -0.35), and the FI-2 (r(s) = -0.29 to -0.47) and disease activity measures (r(s) = 0.36-0.41). Cronbach's alpha coefficients for the 4 subscales varied between 0.85 and 0.95. Weighted kappa coefficients (K(w)) ranged between 0.77 and 0.93 for the 4 subscales and between 0.74 and 0.83 for the 4 single items without systematic variations (p > 0.05). CONCLUSION: This initial validation of the MAP indicates promising measurement properties for assessing limitations in activities of daily living and participation in patients with PM/DM in the United States.
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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 | 0.008 |
| 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 | 0.001 |
| 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".