A systematic review of the effectiveness of occupational health and safety training
Bibliographic record
Abstract
OBJECTIVES: Training is regarded as an important component of occupational health and safety (OHS) programs. This paper primarily addresses whether OHS training has a beneficial effect on workers. The paper also examines whether higher engagement OHS training has a greater effect than lower engagement training. METHODS: Ten bibliographic databases were searched for pre-post randomized trial studies published in journals between 1996 and November 2007. Training interventions were included if they were delivered to workers and were concerned with primary prevention of occupational illness or injury. The methodological quality of each relevant study was assessed and data was extracted. The impacts of OHS training in each study were summarized by calculating the standardized mean differences. The strength of the evidence on training's effectiveness was assessed for (i) knowledge, (ii) attitudes and beliefs, (iIi) behaviors, and (iv) health using the US Centers for Disease Control and Prevention's Guide to Community Preventive Services, a qualitative evidence synthesis method. RESULTS: Twenty-two studies met the relevance criteria of the review. They involved a variety of study populations, occupational hazards, and types of training. Strong evidence was found for the effectiveness of training on worker OHS behaviors, but insufficient evidence was found of its effectiveness on health (ie, symptoms, injuries, illnesses). CONCLUSIONS: The review team recommends that workplaces continue to deliver OHS training to employees because training positively affects worker practices. However, large impacts of training on health cannot be expected, based on research evidence.
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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 | 0.024 | 0.103 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.008 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".