Risk factors for persistent elbow, forearm and hand pain among computer workers
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVES: This study examined the influence of work-related and personal factors on the prognosis of "severe" elbow, forearm, and wrist-hand pain among computer users. METHODS: In a 1-year follow-up study of 6943 computer users, 673 (10%) participants reported "quite a lot" or more trouble due to elbow, forearm, or wrist-hand pain during the 12 months preceding the baseline questionnaire. Pain status (recovery versus persistence) at follow-up was examined in relation to computer work aspects and ergonomic, psychosocial, and personal factors by questionnaire. In addition, data on objectively recorded computer usage were available for 42% of the participants during the follow-up, measured by means of a program (WorkPaceRecorder) installed on their computers. RESULTS: During the follow-up, two-thirds of the baseline cases improved to some degree, but only one-third experienced substantial improvement. The prognosis was not influenced by mouse or keyboard work (time, speed, micropauses, and average activity periods) or ergonomic workplace conditions. Keyboard times, however, were very low. Pain in other regions was a predictor of persistent arm pain. Except for time pressure, female gender, and type-A behavior, the prognosis seemed independent of psychosocial workplace factors and personal factors. A few cases with severe pain were affected at a level which could be compared to clinical pain conditions. CONCLUSIONS: Our results do not support the hypothesis that computer work activity or ergonomic conditions influence the prognosis of severe arm pain. This result is somewhat surprising and should be tested in other studies. Pain in other regions implies a poorer prognosis for arm pain.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it