The impact of work‐related musculoskeletal disorders on workers' caregiving activities
Bibliographic record
Abstract
BACKGROUND: The purpose of the study was to describe and quantify the impact of work-related musculoskeletal disorders on workers' caregiving activities. METHODS: A cross-sectional study was conducted in which a telephone survey was administered to 187 lost-time workers' compensation claimants from Ontario, of whom 49.2% were women. Forty-eight percent of the injured workers were providing unpaid care prior to the injury. RESULTS: Injured workers providing caregiving reported an average reduction in time spent in caregiving activities of 5.5 hr/week, 8 months post-injury. A Sex X Return-to-work status ANCOVA was conducted with difference in caregiving hours as the dependent variable, and with the following covariates: Mean number of caregiving hours, comorbidities, site of injury, and education. Independent of weekly hours of caregiving, decreases in caregiving hours were significantly higher if the worker was a woman or had not returned to work. CONCLUSIONS: Work-related musculoskeletal disorders have a significant impact on workers' time spent in unpaid caregiving activities, an example of the social consequences of occupational injuries. Occupational and caregiving roles are limited by work-related disorders in a parallel fashion.
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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 | 0.002 |
| 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) | 0.002 | 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".