Sensitivity to Change in Systemic Sclerosis of the McMaster-Toronto Arthritis Patient Preference Disability Questionnaire (MACTAR): Shift in Patient Priorities Over Time
Bibliographic record
Abstract
OBJECTIVE: To assess the sensitivity to change of the McMaster-Toronto Arthritis Patient Preference Disability Questionnaire (MACTAR) in systemic sclerosis (SSc) and a shift in patient priorities over time. METHODS: We assessed 49 patients with SSc (8 men) using the MACTAR in a prospective longitudinal study twice or more during annual meetings of the French patient association from 2004 to 2007. Patient-perceived improvement or worsening regarding health status was recorded. Sensitivity to change was assessed by the effect size (ES) and the standardized response mean (SRM) of the MACTAR. RESULTS: The MACTAR global score was significantly increased at followup in the whole group of patients, and the ES and SRM values were -0.37 and -0.34, respectively. These values were similar to those observed for widely used outcome measures for SSc such as the Health Assessment Questionnaire. As defined by the International Classification of Functioning, Disability and Health, the 3 disability domains most often cited at baseline were mobility (7 activities, cited 17 times; 33.3% of patients), domestic life (4 activities, cited 17 times; 33.3% of patients), and community, social and civic life (3 activities, cited 10 times; 19.6% of patients). At followup, 40 patients had changed their first priority and 34 changed 3 priorities. CONCLUSION: The evolution in MACTAR global score over time for patients with SSc reflects longterm general feelings of deterioration. However, shifts in patient priorities are common and may influence the sensitivity to change of the instrument.
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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 | 0.010 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".