Tracking ability in subjects symptomatic of cumulative trauma disorder: does it relate to disability?
Bibliographic record
Abstract
Symptoms of upper extremity cumulative trauma disorders (CTDs) often include weakness, discomfort, pain, numbness and stiffness, which are generally assessed clinically by using static tests or isolated movements. Little is known about the dynamic, functional ability of the upper extremity in CTD, yet, more than impairment, performance variables may relate to disability. The objectives of this study were to determine whether a manual tracking task was sensitive to the presence of symptoms associated with CTD and whether tracking performance related to disability. Forty-five volunteers who had frequently experienced one or more symptoms consistent with upper extremity CTD for at least 1 year and 22 control subjects performed the manual tracking task. Using a hand-held stylus over a digitizing tablet, subjects tracked a target that moved pseudo-randomly and was displayed on a computer screen. The root mean square error of the linear difference between target and stylus positions provided a measure of overall performance accuracy. Quadrant specific performance was also calculated to determine whether the location of the target (hence hand and wrist position) influenced performance. Additionally, the symptomatic group completed the Disability of the Arm, Shoulder and Hand (DASH) questionnaire reflecting physical disability level. Performance accuracy was poorer in symptomatic subjects than controls (p<0.001) and was influenced by target location (p<0.0001). The overall performance was associated with physical disability (r = 0.54). The findings suggest that tracking performance is sensitive to the presence of CTD symptoms and related to disability level. Further validation is required to determine whether the performance measure is sensitive to disease progression or intervention-induced changes.
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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 | 0.000 | 0.006 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".