Mapping hand functioning in hand osteoarthritis: Comparing self‐report instruments with a comprehensive hand function test
Bibliographic record
Abstract
OBJECTIVE: To determine which self-report instruments best explain hand functioning measured by a generic comprehensive hand function test. METHODS: Six questionnaires currently used in hand osteoarthritis (OA), namely, the Arthritis Impact Measurement Scales 2 Short Form (AIMS2-SF), the Australian/Canadian Osteoarthritis Hand Index (AUSCAN), the Cochin scale, the Functional Index of Hand OA (FIHOA), the Health Assessment Questionnaire (HAQ), and the Score for Assessment and Quantification of Chronic Rheumatoid Affections of the Hands (SACRAH), were administered once in 100 patients with hand OA together with the Jebsen-Taylor Hand Function Test (JTHFT). In addition, 3 other hand function tests with short administration time were used: the Moberg Picking-Up Test (MPUT), the Button Test (BT), and grip strength. The Short Form 36 was used to describe health status. The relationship between the instruments and the JTHFT was determined by correlation analyses. RESULTS: AIMS2-SF total scores had the highest raw correlation coefficient to the JTHFT, followed by AIMS2-SF upper body limitation subscale, SACRAH stiffness subscale, and SACRAH total score. If controlled for age, the HAQ had the highest correlation coefficient. Of the 3 short hand function tests, the MPUT showed the highest raw correlation coefficient to the JTHFT; if controlled for age, the BT had the highest correlation coefficient. CONCLUSION: To comprehensively assess hand functioning in patients with hand OA, we recommend using both a self-report instrument used more generally in various arthritides and a self-report instrument specifically developed for hand OA. If a short test is preferred, we recommend using the MPUT or BT.
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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 | 0.008 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".