Upper extremity injured workers stratified by current work status: an examination of health characteristics, work limitations and work instability.
Bibliographic record
Abstract
BACKGROUND: Upper extremity injured workers are an under-studied population. A descriptive comparison of workers with shoulder, elbow and hand injuries reporting to a Canadian Workplace Safety and Insurance Board (WSIB) clinic was undertaken. OBJECTIVE: To determine if differences existed between injury groups stratified by current work status. METHODS: All WSIB claimants reporting to our upper extremity clinic between 2003 and 2008 were approached to participate in this descriptive study. 314 working and 146 non-working WSIB claimants completed the Disabilities of the Arm, Shoulder and Hand questionnaire (DASH); Short Form health survey (SF36); Worker's Limitations Questionnaire and the Work Instability Scale. Various parametric and non-parametric analyses were used to assess significant differences between groups on demographic, work and health related variables. RESULTS: Hand, followed by the shoulder and elbow were the most common site of injury. Most non-workers listed their current injury as the reason for being off work, and attempted to return to work once since their injury occurrence. Non-workers and a subset of workers at high risk for work loss showed significantly worse mental functioning. Workers identified physical demands as the most frequent injury-related on the job limitation. 60% of current workers were listed as low risk for work loss on the Work Instability Scale. CONCLUSION: Poorer mental functioning, being female and sustaining a shoulder injury were risk factors for work instability. Our cohort of injured non-workers were unable to return to work due to their current injury, reinforcing the need to advocate for modified duties, shorter hours and a work environment where stress and injury recurrence is reduced. Future studies examining pre-injury depression as a risk factor for prolonged work absences are warranted.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".