Effectiveness of a participatory ergonomics intervention in improving communication and psychosocial exposures
Bibliographic record
Abstract
A participatory ergonomics programme was implemented in an automotive parts manufacturing factory in which an ergonomics change team was formed, composed of members from management, the organized labour union and the research team. It was hypothesized that the participatory nature of this change process would result in enhanced worker perceptions of workplace communication dynamics, decision latitude and influence, which in conjunction with anticipated mechanical exposure reductions would lead to reduced worker pain severity. Utilizing a sister plant in the corporation as a referent group, a quasi-experimental design was employed with a longitudinal, repeat questionnaire approach to document pre-post intervention changes. Nine participatory activities (psychosocial interventions) were implemented as part of the process. Communication dynamics regarding ergonomics were significantly enhanced at the intervention plant compared to the referent plant. However, there were no significantly different changes in worker perceptions of decision latitude or influence between the two plants, nor did pain severity change. Possible explanations for these results include limited intervention intensity, context and co-intervention differences between the two plants, high plant turnover reducing the statistical power of the study and lack of sensitivity and specificity in the psychosocial measures used. Further research should include the development of psychosocial tools more specific to participatory ergonomic interventions and the assessment of the extent of change in psychosocial factors that might be associated with improvements in pain.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".